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Figueiredo, J.A.F. Gamelas and A.G. 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Men have the highest incidence and mortality related to lung cancer, while in women, it is third by incidence and second by mortality. With exceptions, the five-year survival rate of lung cancer patients is between 10 and 20%, the lowest among most cancer types [2]. Histologically 80–85% of lung cancers are classified as non-small cell lung cancer (NSCLC), while the remaining is small cell lung cancer (SCLC). Adenocarcinoma (LUAD; ~ 65%), squamous cell carcinoma (LUSC; ~ 30%), and large cell carcinoma (LCLC) are the major subtypes of NSCLC and originates from different types of lung cells [1, 3, 4]. While SCLC is less frequent but more aggressive as compared to LUAD and LUSC. NSCLC is mainly treated by surgery, chemotherapy, radiation, or targeted therapy but with dismal lung cancer survival outcomes. There has been extensive progress in aiming targeted drug delivery towards cancer cells; the accuracy, efficacy, and success are often limited by resistance developed by tumor cells and inter-subject variability. Low therapeutic indices, differences in health effects, and toxicity from chemotherapeutic agents are some of the drawbacks of current NSCLC treatment. This has prompted researchers to explore other cancer treatment options, keeping in mind individual patient’s genetic responses and adverse drug reactions (ADR) to chemotherapeutic agents as ‘pharmacogenetics’ studies [5].
Pharmacogenetics is an evolving branch of pharmacology that examines the genetic variation between individuals and its correlation with their response to drugs/pharmaceuticals and other xenobiotics. In comparison, pharmacogenomics encompasses all genes in the genome that modulates drug response. The awareness of the genetic heterogeneity in oncology is of significant importance, owing to the limited therapeutic index of cancer therapies and the possibility of ADR-associated life-threatening complications. Within an individual and comparison among NSCLC patients, genomic alterations are major reasons for variations in chemotherapeutic drug response and related toxicity [6]. Studies on NSCLC genetic and molecular alterations provide new targets for treatment, help in the identification of biomarkers for early diagnosis, and helps to predict patient prognosis and progression [7]. NSCLC genetic polymorphism can act as either predictive or prognostic markers [8]. Single-nucleotide polymorphisms (SNPs) or a single nucleotide substitution can affect the expression or functionality of essential enzymes and/or targets in the metabolism and activity of anticancer drugs. Genetic polymorphism is extensively investigated as a prognostic or predictive factor in various tumor types, including NSCLC [9].
Further, pharmacogenetics also helps to prevent cancer-related mortalities by forecasting pre-symptomatic diagnosis, designing customized or tailor-made dosage regimens for individuals, and optimization of a therapeutic window of antineoplastic drugs on a personalized basis. However, pharmacogenetics is an evolving arena in cancer treatment and has obvious underlying limitations that need to be investigated. Determination of genetic variants has primarily relied on SNP, although lately, haplotypes of SNPs and non-genetic factors (like age, lifestyle, diet, profession, and intestinal microflora) are included in studies. Nonetheless, an additional challenge in pharmacogenetics for treating NSCLC deals with validation and standardization of genotyping procedures that are a major deciding factor in the personalization of cancer therapy. Many therapeutic interventions can be utilized for pharmacogenetics-associated NSCLC treatment. The examples include, but not restricted to chemotherapeutic agents (cisplatin, gemcitabine, pemetrexed, taxanes, etc.), immune checkpoint inhibitors [programmed cell death 1 (PD-1), cytotoxic T-lymphocyte protein 4 (CTLA-4)], and a combination of immunotherapy with chemotherapy [10]. This chapter throws light on the current status of pharmacogenetics-based therapeutics in NSCLC with a focus on genetic alterations by gene mutations, exploration of possible treatment modalities, challenges involved, and prospects of pharmacogenetics in treating NSCLC.
Human Genome Project (HGP) has revealed that the genetic composition of humans is 99% similar, with only 1% variations leading to individual differences. This clarifies why individuals show a difference in response to anticancer drugs concerning drug pharmacology, toxicity, and controlling proliferation, invasion, and metastasis of tumor cells in NSCLC [11, 12]. Simultaneously, several studies have suggested a personalized medicine approach to achieving maximum efficacy and minimum toxicity of anticancer drugs using pharmacogenetics to target NSCLC [12]. Thus, NSCLC patients’ categorization based on underlying genetic and molecular alterations can help in personalizing anticancer drugs and dosage regimens. Therapy tuned to individual patient’s genotypic and phenotypic landscape can achieve the highest therapeutic benefits [13]. The complete knowledge of driver mutation pathways and biomarkers can explain NSCLC heterogeneity for identifying personalizing therapies. Information about driver mutation frequency and associated functional changes can help decipher actionable, personalized molecular targets. Therefore, a brief description of the critical driver genes that frequently undergo mutations-associated with lung cancer (Figure 1).
Comparison of genetic changes in major oncogenic pathways in individuals with LUAD, LUSC, and SCLC and the frequencies are shown in the specific boxes. The genetic alterations data is a sum of somatic defects, homozygous deletions, focal amplifications, and major changes of gene expression. Reproduced from Salehi-Rad et al. [
NSCLC is a heterogeneous disease, and recent sequencing studies have revealed the genomic landscape (Figure 1). Common genomic alterations in LUAD include KRAS, EGFR, HER2, MET, RET, ALK, and ROS1, while the important alteration in tumor suppressor includes TP53, KEAP1, LKB1, and NF1 (Figure 1) [1, 14]. Interestingly the major genomic alterations in LUSC include TP53, PIK3CA, CDKN2A, NFE2L2, KEAP1, SOX2, PTEN, CDKN2A, RB1, CCND1, NOTCH1, MLL2, and HLA-A (Figure 1) [1, 15] (Figure 1). Inhibitors of these genes are primarily used as a treatment procedure and as one of the targeted therapies. Several driver oncogenes involved in NSCLC have been identified to be targeted with prior information of molecular testing and individual patient’s pharmacogenetics towards drugs employed. Examples of such targets include EGFR, ALK, KRAS, BRAF, ROS 1, PTEN, HER 2, MET, and FGFR, identified in some patient subsets of NSCLC as potential treatment targets [16].
EGFR (HER1 in humans) is part of the ErbB family of receptor tyrosine kinases (RTKs). Intracellular signaling occurs when RTKs are bound extracellularly to form homo or heterodimers [17]. Clinically significant mutations occur within the tyrosine kinase domain and are associated with drug sensitivity. The genetic alteration, including mutation or amplification in EGFR, results in increased tumoral metastasis, angiogenesis, and proliferation. Multiple mutations in the EGFR tyrosine kinase domain (deletion exon 19, L858R in exon 21) are associated with NSCLC. ATP-competitive TKIs bind to EGFR and yield promising clinical outcomes. Though targeted therapy for most EGFR mutations has produced better clinical outcomes, T790M mutation inhibition in EGFR resulted in resistance to targeted therapy [18]. Three generations of TKI have been reported for personalized NSCLC precision therapy based on patient pharmacogenetics; first-generation examples being gefitinib and erlotinib, second-generation Afatinib, and Neratinib while the third generation includes osimertinib [12]. Afatinib is an irreversible TKI, which has a unique property that, unlike other TKIs it does not require CYP3A4 activity in the liver for its targeted anticancer action. Thus, NSCLC patients with pharmacogenetics of deficient or abnormal CYP3A4 activity can be treated with afatinib over other established TKIs [19].
A fusion gene of anaplastic lymphoma kinase (ALK) with echinoderm microtubule-associated protein-like 4 (EML4) (EML4-ALK) is prevalent in 3–5% NSCLC patients. EML4-ALK variants act as driver mutations and modulate the JAK/STAT, PI3K/AKT, and MAPK pathways, thereby provide proliferative and survival advantages to the cancer cells. Crizotinib blocks the kinase activity of the EML4-ALK and induces cancer cell apoptosis. ALK fusion is also familiar with other genes, including HIP1, KIF5B, KLC1, DCTN1, PTPN3, STRN, and show association with NSCLC. Individuals with NSCLC having significant ALK rearrangements can be genetically identified with advanced techniques like comprehensive next-generation sequencing (NGS), immunohistochemistry, and in-situ fluorescence hybridization (FISH). In advanced NSCLC stages, ALK TKIs have confirmed the progression-free survival of patients with better prognoses. Several second-generation ALK inhibitors can help target ALK-positive NSCLC, such as alectinib, ceritinib, and AP26133 developed and are currently under evaluation in clinical trials [20]. ROS1 rearrangements are observed in 1–2% of NSCLC patients. ROS 1 is a receptor tyrosine kinase and is structurally homology to ALK protein and serves as the basis of using ALK inhibitors to target ROS1+ NSCLCs. Crizotinib and entrectinib are FDA approved and show a quick positive response by slowing cancer progression in ROS-1+ NSCLC [21].
BRAF encodes a threonine/serine protein kinase that is an effector protein of KRAS. BRAF activates the MAPK signal transduction, which regulates cell proliferation and survival. Mutations in BRAF are about 1 to 3% in NSCLC, with a predominance of V600E (50%), G469A (39%), D594G (11%), and K601E, G469S, G596R, G466R, and T599dup [21]. Dabrafenib is a BRAF inhibitor combined with trametinib (MEK inhibitor), is FDA approved for BRAF V600E+ metastatic NSCLC. Vemurafenib, another BRAF inhibitor, showed a 42% overall response rate for BRAF V600E+ NSCLC in a basket trial.
KRAS encodes a G protein and is a member of the RAS proto-oncogene family. KRAS-GTP complex activates the RAS/MAPK, PI3K/mTOR, and RalGDS-RalA/B signaling pathways and regulates cell proliferation, differentiation, and survival. Mutations in KRAS are recurrent in NSCLC (25–40%), especially LUAD. Ras gene and three forms are present H-Ras, N-Ras and K-Ras. In general, KRAS mutations have a poor prognosis. Out of KRAS mutations, G12C, G12V, G12D, and G12A are common and more frequent in male smokers. Common mutation among smokers is G12C (about 41%), while in nonsmokers, it is G12D (56%) and G12V. Though compounds are discovered that target the GDP-binding pocket (ARS-853, SML-8-73-1) but the efficacy and toxicity have been a hurdle. Currently, there is no specific developed FDA-approved anticancer agent that uniquely targets KRAS; however, MEK and PI3K/mTOR/MEK inhibitors are thought to be selective in the inhibiting downstream targets of KRAS mutant cases [22]. KRAS gain-of-function mutations serve as predictive markers for NSCLC chemotherapy, but recent studies present a geographical bias. KRAS mutations are frequent amongst westerns (30%) compared to Asian (10%) LUAD patients [23]. Moreover, the prognostic and predictive response is more efficient in LUAD than other NSCLC subtypes, and proper clinical pharmacogenetic evaluation and implementation is needed.
HER2 (ERBB2) is a proto-oncogene, encodes for tyrosine kinase receptors, and relies on heterodimerization for activation with receptors from the EFGR family. Upon activation, HER2, in turn, triggers downstream signaling like PI3K/mTOR, RAF/MEK/ERK, and the MEK/JNK pathways and regulates cell proliferation, differentiation, and migration. HER2 genetic alteration not only drives several tumors (breast and gastric cancer) but also plays a crucial role in NSCLC formation. HER2 amplification and overexpression are associated with 7–34.9% of NSCLCs and are related to poor prognosis. Activating mutations (like HER exon 20) are observed in 2–4% of NSCLCs cases, especially in LUAD [24]. The mutations in the tyrosine kinase domain are investigated as attractive therapeutic targets in NSCLC. Targeted therapy against HER2 (TKIs and antibody) is under clinical investigation, and the value of HER2 for such patient screening is gaining precedence. HER2-targeted TKIs, include afatinib, ipatinib, neratinib, and pyrotinib, while trastuzumab and T-DM1 conjugate are antibody-based [25].
RET proto-oncogene encodes for an RTK, localized to chromosome 10, and activates replication, cell proliferation, motility and differentiation. The GDFN family ligand (GFL) interaction with GDFN-family receptor α (GFRα) initiates RET receptor protein dimerization and formation GFL-GFRα-RET heteromeric complex. The complex formation results in RET activation and downstream signaling via RAS/RAF/MEK/ERK or PI3K/AKT1/mTOR pathways. Abnormal RET signaling may lead to cancerous growth and have a driver potential. RET Rearrangements are common in lung cancers (1–2%). RET fusions are common in NSCLC with partner genes like kinesin family member 5B (KIF5B), coiled-coil domain containing 6 (CCDC6), tripartite motif-containing 33 (TRIM33), Cut like homeobox 1 (CUX1), nuclear receptor coactivator 4 (NCOA4), and KIAA1468 [26]. Selpercatinib, a TKI that is FDA approved for use in RET+ NSCLC [27]. Other TKIs like vandetanib, cabozantinib, sorafenib and sunitinib can inhibit activated RET signaling and tumorigenic transformation. Activating RET mutations like M918T and acquired RET mutations (G810R, G810S, and G810C) in response to selpercatinib treatment is also reported in NSCLC [28]. Thus, RET is an interactive target and a biomarker for NSCLC.
Other actionable biomarkers in the lung include MET, PI3KCA, NTRK1, FGFR2, and DDR2 and are explained in detail elsewhere [29]. As driver mutations affect specific and exclusive cellular pathways to cause cancer, opportunities are being explored for targeted drug therapies towards various mutating genes associated with NSCLC, as mentioned in Table 1.
Target gene (% mutation frequency) | Genetic alterations | Mutation effect | Drugs employed | References |
---|---|---|---|---|
EGFR [10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25] | Mutation | ↑ angiogenesis, proliferation and metastasis | Gefitinib, Erlotinib, Afatinib, Neratinib, Osimertinib | [14] |
EML4-ALK [2, 3, 4] | Fusion | ↑ proliferation, migration and survival | Alectinib, Crizotinib, Ceritinib, | [30, 31] |
ROS 1 [2, 3] | Fusion, rearrangement | ↑ cell survival and resistance | Crizotinib and Foretinib | [32] |
KRAS [2, 3, 4, 5] | Mutation | ↑ Chemotherapy resistance, survival and proliferation | Sorafenib, Ridaforolimus, Selumetinib + Docetaxel | [33] |
MET [1, 2] | Amplification, exon 14 skipping | ↑ proliferation and metastasis | Cabozantinib, Crizotinib Ornatuzumab, Tivantinib | [34] |
BRAF [2, 3] | Mutation | ↑ Proliferation, and survival, ↑ Resistance to EGFR inhibitors | Sorafenib, Debrafenib | [35] |
RET | Fusion, rearrangement | ↑ Proliferation | Carbozantinib, Ponatinib, Vandetanib | [13] |
FGFR 1 | Amplification | ↑ chemo resistance proliferation and survival | Dovitinib Nintedanib, Ponatinib | [36] |
PTEN | Deletion and mutation | ↑PI3K signaling, survival and proliferation | PI3K inhibitors | [37] |
PIK3CA [1, 2, 3] | Mutation | ↑ Metastasis and survival | Buparlisib, inhibitors for AKT | [38] |
TP53 [30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50] | Mutation | ↓ apoptosis, ↑ Growth | — | [39] |
DDR2 | Mutation | ↑ invasion and Cell migration,, proliferation and survival | Dasatinib | [40] |
CDKN2A | Deletions | ↑ Cell growth | — | [41] |
HER2 [5, 6, 7, 8, 9, 10] | Mutation | ↑ Amplification | Afatinib, Dacomitinib, neratinib, Trastuzumab | [16] |
Mutating genes associated with NSCLC, mechanism of mutation with its effects, and targeted therapy.
NSCLC is a widely prevalent and challenging health problem for the human race. Despite rapid advances in lung cancer treatment, it is still one of the leading causes of death worldwide. Traditional chemotherapeutic approaches failed to yield satisfactory results in terms of treatment outcome. Interestingly, the association of genetic variations with treatment outcome of some of the most commonly used chemotherapeutic drugs has opened new vistas in the domain of lung cancer treatment [12]. The relatively new area of Pharmacogenetics aims to correlate the association between genetic variations and drug effects and formulate a rational personalized drug treatment offering minimum side effects and maximum efficacy [42]. The inherited genetic variations such as single-nucleotide polymorphisms (SNPs) have been primarily studied, most commonly focusing on the candidate gene approach. These genetic changes can either lead to the altered expression or function of drug-metabolizing enzymes or their targets, thereby modulating the activity of chemotherapeutics [43].
Pemetrexed is a commonly used folate antimetabolite, a multi-targeted anti-cancer drug used in NSCLC treatment. Pemetrexed causes inhibition of critical enzymes in the folate pathway including, thymidylate synthase, dihydrofolate reductase, and glycinamide ribonucleotide formyl transferase leading to a reduction in folate depletion resulting in altered purines and pyrimidines synthesis [44]. Thymidylate synthase (TS) expression is associated with the treatment outcome, especially in nonsquamous carcinoma patients treated with pemetrexed-based chemotherapy [45]. Studies conducted on the role of polymorphisms in TS, such as polymorphic tandem repeats located in the TS enhancer region (TSER), provide conflicting results. While some studies have observed that increased expression of TS with three copies (TSER*3) of the R than with two copies (TSER*2) is associated with treatment outcome in lung cancers, other studies did not observe such an association [46]. However, the homozygous variant T677 T of methylenetetrahydrofolate reductase was associated with prolonged progression-free survival compared to the wild-type or heterozygous genotype. The observation could be due to increased TS inhibition by pemetrexed due to the polymorphic variant since methylenetetrahydrofolate reductase is an essential regulator of folate homeostasis.
The entry of pemetrexed into the cells is mediated by the reduced folate carrier (RFC). A study investigating the combined action of pemetrexed and bevacizumab suggested the role of polymorphisms in RFC exon6 and progression-free survival. A similar association was also observed with IVS7 (1478) polymorphism in glutamyl hydrolase (GGH) while GGH IVS2 (1307) CC genotype was associated with significantly longer overall survival [47]. On the contrary, no association was observed with the outcome for GGH IVS7 (1478) and IVS2 (1307) in a randomized phase II trial involving fifty four patients for treatment with pemetrexed and gemcitabine [48]. The study also reported an association of RFC-exon6-SNP with outcome following treatment with pemetrexed.
The tyrosine kinase inhibitor (TKI) family has been clinically successful as an anti-cancer strategy. An enhanced expression of EGFR leads to the activation of pathways and proto-oncogenes that can lead to lung cancer development. For the EGFR gene, most of the studies have focused on polymorphisms present in regions regulating the expression, such as those present in the 5′-flanking region and intron-1. Two important SNPs located in the transcriptional start site of the promoter region of EGFR are −191C/A and − 216G/T. The −191C/A polymorphism causes enhanced EGFR expression and activity, while the −216G/T genotype, located at the binding site for the transcription factor Sp1, increases mRNA expression. However, the A-G variant, causing substitution of an arginine with a lysine at codon 497 (R497K), leads to the reduction of EGFR activity [49]. All three polymorphisms were evaluated for association with gefitinib treatment response in advanced NSCLC patients. Out of the three polymorphisms, the −216G/T variant showed a significant association with prolonged progression-free survival, high rates of stable disease/partial response, and treatment-related side effects such as rash and diarrhea [50].
Another EGFR polymorphism present in intron one was also reported to play an important role in the treatment outcome of gefitinib for NSCLC in different ethnic groups. The dinucleotide polymorphism is associated with a variable number of CA repeats in NSCLC. Upon gefitinib-treatment, it was observed that a smaller number of CA repeats was associated with increased EGFR transcription and better survival. This was observed in both Asian and Caucasian populations. For instance, studies conducted in Chinese patients treated with gefitinib reported better responses in NSCLC patients with shorter CA repeats (less than 16 repeats) [51]. However, the results were inconsistent in Caucasian patients as no association was observed for CA repeats and clinical outcomes in patients treated with gefitinib [52]. Similar observations were also made in a study involving advanced NSCLC patients treated with erlotinib [53].
Genetic polymorphisms in Protein kinase B (AKT1), DNA repair pathway genes like ATP-binding cassette superfamily G member 2 (ABCG2) also play an essential role in determining the treatment outcome in NSCLC patients. In studies involving the Caucasian populations, lower Akt protein levels were observed associated with haplotype having two polymorphisms (SNP3 and SNP4). The same haplotype was also found associated with lower rates of apoptosis-induction by radiation in EBV-transformed lymphoblastoid. In another Caucasian study involving NSCLC patients treated with gefitinib, AKT1-SNP4 A/A genotype was associated with shorter overall survival while AKT1-rs2498804 GT and GG alleles resulted in metastases in the brain [54]. Similar observations were also made in a Korean study where it was observed that in NSCLC patients, several genetic variations in the PI3K/AKT pathway served as a useful marker in response to various chemotherapeutic drugs [55].
ABCG2 is a member of the ATP-binding cassette (ABC) transporter family and plays a crucial role in the absorption and elimination of gefitinib. ABCG2 binds gefitinib and is expressed at higher levels in the gastrointestinal tract. Polymorphisms in ABCG2 could affect the metabolism of gefitinib due to variations in expression, function, and localization of ABCG2. One such polymorphism, ABCG2 421C/A (Q141K), has been found to be associated with a decreased protein expression and associated activity of ABCG2, resulting in the accumulation of both gefitinib and erlotinib [56] though conflicting reports are also available.
Investigators have also explored the association of selected genetic variations with toxicity caused by EGFR-TKIs, such as rash and diarrhea. In a study involving 52 NSCLC patients undergoing treatment with gefitinib, different intron-1 CA repeat variants were found to be associated with varying grades of skin rash [57]. Similarly, studies have also reported the association of genetic variations in EGFR and ABCG2 with diarrhea in patients undergoing treatment with gefitinib. Examples of such variants are EGFR 191C/A and A/A, EGFR 216G/G, R497K A/A, and ABCG2 421C/A variant [50, 58]. However, another study failed to find such an association with ABCG2 421C/A, though moderate–severe diarrhea was found to be associated with ABCG2 15622C/T polymorphism and the ABCG2 (1143C/T, −15622C/T) haplotype [59]. A category of enzymes that play an essential role in the metabolism of chemotherapeutics is cytochrome P450s. Commonly used anti-cancer drugs used in the treatment of NSCLC such as gefitinib and erlotinib are metabolized by the CYP3A4, CYP3A5, and CYP1A isozymes. However, erlotinib but not gefitinib is metabolized by CYP1A2. CYPs also exhibit a large number of genetic variations, which results in different pharmacokinetics of TKIs in NSCLC patients. In cases undergoing treatment with erlotinib and having skin rash due to A/A variant of CYP3A4 resulting in lower CYP3A4 expression [60]. The same study also reported the association of CYP3A5*3 G polymorphism with grade ≥ 2 rash and diarrhea.
The ALK gene, encoding a TK receptor, gets fused with echinoderm microtubule associated protein like 4 (EML4), leading to the development of lung cancer. The fusion gene EML4-ALK encodes a fusion protein that leads to the constitutive activation of ALK kinase as a result of oligomerization of ALK in absence of the ligand. Crizotinib is a commonly used ALK-inhibitor drug that targets lung cancer caused as a result of the EML4-ALK fusion protein. It acts as a ATP-competitive inhibitor and binds to the ATP binding pocket necessary for kinase activity leading to carcinogenesis [61]. The role of ALK gene mutations in determining the treatment outcome in lung cancer patients receiving Crizotinib was brought to light when it was observed that a male patient of lung cancer developed resistance to the drug after an excellent initial response [62].
Further investigations revealed that the cause of resistance was two mutations in the ALK gene (C1156Y and L1196M). The observations were validated by an
Apart from the conventional chemotherapeutic agents used for the treatment of NSCLC, immune checkpoint inhibitors (ICIs) have gained much attention in recent times. Though our immune system can target the cancer cells, yet cancer cells escape this immunosurveillance and destruction. The main hallmark of anti-tumor immune response is T cell-mediated identification of tumor-specific antigens. Tumor cell often activates immune checkpoints to effect an immune escape. Programmed cell death protein 1 (PD-1/CD279) and cytotoxic T-lymphocyte protein 4 (CTLA4) are the best-studied checkpoint inhibitors. Programmed cell death ligand-1 (PD-L1) expression, especially by tumor cells, can inhibit the response of PD-1 expressing effector T cells and induce T cell exhaustion. Treatment using anti-PD-1 or anti-PD-L1 antibody causes checkpoint blockade and thereby releases the inhibitory brake on anti-tumor effector T cell function [65, 66]. The approved monoclonal antibodies for targeting PD-1 are nivolumab and pembrolizumab while the anti-PDL1 antibodies are atezolizumab and durvalumab for lung cancer treatment [67]. The effects of pembrolizumab may be influenced by two possibilities: change in its binding site on the receptor or genetic changes that may reduce the immune system’s capability to target cancer cells. A study conducted on cases showing resistance against pembrolizumab did reveal mutations that inactivated Janus kinase1 (JAK1), Janus kinase2 (JAK2), and β2 microglobulin (B2M). The data indicated that the immunological pathways were affected by the mutations [68].
CTLA-4, also known as CD152, is a receptor expressed on the surface of lymphocytes and fibroblasts. This receptor on the surface of T lymphocytes competes with CD28 (co-stimulatory receptor) to bind to the B7 ligands CD80 and CD86, expressed on the surface of antigen-presenting cells. Since the CTLA4 receptor has a higher affinity for binding to the B7 ligands, it inhibits the binding of CD28, which leads to the decreased production of the cytokine IL-2 and ultimately prevents the activity of the Cancer-Immunity Cycle (CIC) [69]. Thus, inhibition of CTLA4 checkpoint can lead to the suppression of binding between CTLA4 receptor and ligand B7. This will boost the clearance of cancer cells by activating the innate and adaptive components of the immune system. US FDA has already approved ipilimumab and tremelimumab as immune checkpoint inhibitors targeting the CTLA4 for patients with metastatic melanoma. Moreover, studies are going on with immune checkpoint inhibitors targeting the CTLA4 for NSCLC and may deliver promising results [70].
The field of immunotherapy has shown significant advancements in the treatment of several cancers, including NSCLC. However, the success is also accompanied by serious challenges, particularly in NSCLC. Some NSCLC patients show primary resistance and are unresponsive to ICIs, while others develop secondary resistance during/after the treatment. Moreover, a unique spectrum of immune-related adverse events (IRAEs) also limits the use of ICIs. The mechanism governing both the primary and secondary resistance needs further investigation. Immunopharmacogenomics can explain these resistance mechanisms. The current phase III studies of PD-1 and PD-L1 inhibitors, either alone or in combination with conventional approaches in different stages of NSCLC, will serve to improve the treatment outcome significantly [1]. However, there are still many challenges ahead though immunotherapy with checkpoint inhibitor has already raised new hopes of novel treatment modality with better and more effective treatment outcomes for NSCLC patients.
Lung cancer is one of the leading causes of cancer-related death worldwide, with a 5-year survival rate of approximately 15%, suggesting a comprehensive genomic alteration map may help. The lack of an early diagnosis and inefficiency in conventional therapies causes poor prognosis and lung cancer patients’ overall survival. Moreover, pharmacogenetic trials ended in conflicting and inconclusive data because of non-standardized methodologies, sample heterogeneity, clinical sample processing techniques, and the inadequate number of enrolled individuals. Clinical sample preparation protocols are varied and challenging to follow in a clinical setting. Collection of needle biopsy of lung tumor is a challenge in itself. The tumor cores are usually retained as Formalin-Fixed Paraffin-Embedded (FFPE) tissue specimens. Defining the normal tissue needs more attention than we think. Recent findings suggest that normal-looking tissue adjacent to the tumor may be existing in an intermediate state. Considering tumor variability, it is unclear whether core biopsies are indicative of the oligoclonal nature of NSCLC? Data generated from specific experiments suggest histological markers can vary significantly and therefore contributing to sequence data heterogeneity within and amongst various studies. Another aspect related to biomarkers is robustness, sensitivity, and false-positive assessment of the molecular diagnostic, especially regarding immune checkpoint therapy.
Lack of pharmacogenetics biomarkers is another challenge for NSCLC pharmacogenetics. Biomarkers are significant in drug development and are used to measure the investigational drug effects on people. Cancer biomarkers are essential for diagnosis, risk assessment, the staging of cancer, screening, patient stratification, prognosis, and predict the impact of the therapy [71]. The selection of cytostatic drugs is based on the estimated responsiveness as per the predictive molecular biomarkers. In NSCLC, the predictive biomarkers that are providing for targeted therapy include EGFR and ALK. As an example, FDA-approved drugs like afatinib are associated with biomarker EGFR, and ceritinib is related to the biomarker ALK. Other essential genomic alterations in key genes like KRAS, ROS1, MET, NTRK1, FGFR, BRAF, PI3KCA, RET, PTEN, and DDR2 provide valuable information (Figure 2). The REMARK (Reporting Recommendations for Tumor Marker Prognostic Studies) guidelines provides criterion and suggestions for designing prognostic and tumor biomarker studies [72]. Several NSCLC studies still do not follow and comply with the standardization protocols of REMARK, thus obfuscating the clinical use scenario of biomarkers. Many trials do not include biomarker analysis as a criterion for including patients, especially in NSCLC, and serves as a significant challenge by creating selection bias. Tumor prognostic biomarker staining (for TUBB3) and scoring was done in a fraction of NSCLC in the N + IFCT-0002 trial [73].
Representation of biomarkers and targeting drug acting on the same.
Immune checkpoint therapy relies on monoclonal antibodies and may mediate a variety of adverse hypersensitivities, including anaphylaxis (type I), cytotoxic (type II), immune (type III), and T cell-mediated (type IV) reactions [74]. The Discovery of predictive biomarkers for immune-associated adverse reactions are essential pharmacogenetic needs for personalized cancer therapy. Genetic polymorphism, especially in the genes associated with antibody recognition, presentation, and immune response, may affect the efficacy. The role of polymorphism concerning the metabolism of therapeutic antibodies can alter antibody half-life and therapeutic response. Genotypic variation in the PD-L1 (rs4143815 C/C and C/G genotype in comparison to G/G phenotype) show higher progression-free survival upon treatment with nivolumab in NSCLC [75]. A study conducted by Rizvi et al. showed a correlation of pembrolizumab efficacy with an increased nonsynonymous somatic mutational burden. A higher mutational burden was associated with an expanded neo-antigen repertoire and effective T cell-specific response [76, 77]. The Discovery of personalized biomarkers for risk assessment, detection, diagnostic, prognostic, and monitoring can be crucial in tailored NSCLC therapy. Pharmacogenetic studies correlating genetic alterations regarding immunotherapy are yet to be correctly established.
In this modern world of fast-growing medicine and research, treatment is not just about curing an aliment but also providing a better standard of life and living. With new social standards, smoking habits, and environmental pollution, NSCLC diagnoses are projected at approximately 116,660 women and 119,100 men in 2021. To treat lung cancer, it is essential to identify the disease at the earliest. The Discovery of NSCLC biomarkers can help identify disease susceptibility and aid in disease screening, diagnosis, prognosis, prediction of response, and monitoring disease recurrence. Recent advances in novel detection techniques like high throughput omics technology, multiplexed immunofluorescence microscopy, bioluminescence resonance energy transfer (BRET), CRISPR-based biosensors, surface-enhanced Raman spectroscopy have generated hope for better treatment. Bulk and single-cell next-generation sequencing (NGS), circulating cell-free DNA (cfDNA), single-cell proteomics can help in biomarker discovery and push modern pharmacogenetics and personalized medicine. Discovery strategies including hotspot panels (frequently observed gene mutations), Actionable gene panels (targeted gene exons), disease-focused panel (genes involved in a disease), comprehensive panels (correlative genes), and validated panels (tested genes) NGS applications can reduce biomarker discovery time. Machine learning-based data analyses platforms and algorithms may help undertake candidate polymorphism search; candidate pathway searches better predict correlations between gene alterations and therapeutic response.
Exploring new molecular signature-based personalized medicine can open up future potential healthcare environments. Considering the massive expansion in NGS-based NSCLC molecular data generation, integrating pharmacogenetics and genomic knowledge with the potential of theranostics can lead to effective therapy. Theranostics, the fusion of therapeutics and diagnostics, using a nanotechnology-based delivery platform can pave the way to precision and personalized medicine [78]. Nanotechnology is a quickly evolving biomedical research area and has been used to address several biological issues, including therapeutics and diagnostics [79]. Nanoscale-based delivery platforms like liposomes, polymeric nanoparticles, metal nanoparticles, and bio-nano particles can be efficiently used for theranostic applications for targeting cancer. Nanoparticle offers a benefit over standard medicinal therapies regarding biocompatibility, enhanced permeability retention, higher drug loading, targeting precision, a significant degree of versatility, and real-time monitoring of the disease [80]. Nanoparticle-based nanotheranostics can provide multifunctional benefits including, imaging, prognostic, diagnostics, and monitoring therapeutic outcome in NSCLC patients. Mukherjee et al. presented a detailed analysis of lung cancer theranostics [4].
Liquid biopsy and microfluidic technology can help in early disease detection. NGS has already helped identify new cancer-driving mutations, and this has encouraged scientists for drug repurposing. Scientists are deciphering synthetic lethality interactions, where two or more gene simultaneous alteration in the presence of a therapeutic may lead to lethality. Efficacy of immune checkpoint therapies is associated with genotypic variance, and immune-based biomarkers may provide a clear understanding of immunepharmacogenetics. Big data analyses of the growing pharmacogenetic or pharmacogenomic dataset can soon lead us to personalized NSCLC therapeutics.
Dr. Manash K. Paul acknowledges Professors, Steven Dubinett, Brigitte Gomperts and Volker Hartenstein for providing continuous support and mentoring.
The authors declare no conflict of interest. The authors have no other pertinent affiliations or financial connection with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
Conceptualization - MKP; writing original draft preparation - MR, KM, SS, PA, MKP; Review and editing - MKP.
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Dariva and Alexandre F. Galio",authors:[{id:"169261",title:"Dr.",name:"Camila",middleName:"G.",surname:"Dariva",slug:"camila-dariva",fullName:"Camila Dariva"},{id:"170138",title:"Dr.",name:"Alexandre",middleName:"Ferreira",surname:"Galio",slug:"alexandre-galio",fullName:"Alexandre Galio"}]},{id:"44359",doi:"10.5772/56197",title:"Microstructure and Mechanical Properties of High Strength Two-Phase Titanium Alloys",slug:"microstructure-and-mechanical-properties-of-high-strength-two-phase-titanium-alloys",totalDownloads:10319,totalCrossrefCites:57,totalDimensionsCites:129,abstract:null,book:{id:"3494",slug:"titanium-alloys-advances-in-properties-control",title:"Titanium Alloys",fullTitle:"Titanium Alloys - Advances in Properties Control"},signatures:"J. Sieniawski, W. Ziaja, K. Kubiak and M. 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L. Sukiman, X. Zhou, N. Birbilis, A.E. Hughes, J. M. C. Mol, S. J. Garcia, X. Zhou and G. E. Thompson",authors:[{id:"43567",title:"Prof.",name:"Nick",middleName:null,surname:"Birbilis",slug:"nick-birbilis",fullName:"Nick Birbilis"}]},{id:"24059",doi:"10.5772/18766",title:"High Strength Al-Alloys: Microstructure, Corrosion and Principles of Protection",slug:"high-strength-al-alloys-microstructure-corrosion-and-principles-of-protection",totalDownloads:6900,totalCrossrefCites:10,totalDimensionsCites:57,abstract:null,book:{id:"217",slug:"recent-trends-in-processing-and-degradation-of-aluminium-alloys",title:"Recent Trends in Processing and Degradation of Aluminium Alloys",fullTitle:"Recent Trends in Processing and Degradation of Aluminium Alloys"},signatures:"Anthony E. Hughes, Nick Birbilis, Johannes M.C. Mol, Santiago J. Garcia, Xiaorong Zhou and George E. Thompson",authors:[{id:"43567",title:"Prof.",name:"Nick",middleName:null,surname:"Birbilis",slug:"nick-birbilis",fullName:"Nick Birbilis"},{id:"32486",title:"Prof.",name:"Anthony",middleName:"E",surname:"Hughes",slug:"anthony-hughes",fullName:"Anthony Hughes"},{id:"43568",title:"Prof.",name:"Arjan",middleName:null,surname:"Mol",slug:"arjan-mol",fullName:"Arjan Mol"},{id:"43569",title:"Prof.",name:"Santiago",middleName:null,surname:"Garcia Espallargas",slug:"santiago-garcia-espallargas",fullName:"Santiago Garcia Espallargas"},{id:"43570",title:"Prof.",name:"Xiaorang",middleName:null,surname:"Zhou",slug:"xiaorang-zhou",fullName:"Xiaorang Zhou"},{id:"83528",title:"Prof.",name:"George",middleName:null,surname:"Thompson",slug:"george-thompson",fullName:"George Thompson"}]}],mostDownloadedChaptersLast30Days:[{id:"12751",title:"Contemporary Forming Methods of the Structure and Properties of Cast Magnesium Alloys",slug:"contemporary-forming-methods-of-the-structure-and-properties-of-cast-magnesium-alloys",totalDownloads:3109,totalCrossrefCites:0,totalDimensionsCites:0,abstract:null,book:{id:"27",slug:"magnesium-alloys-design-processing-and-properties",title:"Magnesium Alloys",fullTitle:"Magnesium Alloys - Design, Processing and Properties"},signatures:"Leszek A. Dobrzański, Tomasz Tański, Szymon Malara, Mariusz Król and Justyna Domagała-dubiel",authors:[{id:"15700",title:"Prof.",name:"Tomasz Arkadiusz",middleName:null,surname:"Tański",slug:"tomasz-arkadiusz-tanski",fullName:"Tomasz Arkadiusz Tański"},{id:"15880",title:"Prof.",name:"Leszek A.",middleName:null,surname:"Dobrzański",slug:"leszek-a.-dobrzanski",fullName:"Leszek A. 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The freezing pattern of the liquid melt decides the feeding of the mould which is instrumental in producing a complete and compact casting. For pure metals and even in case of alloys with a narrow freezing range a well defined solid–liquid macro-interface exists. Here feeding of the solidifying casting is the easiest, by the common lowering of the liquid metal surface in the mould. However, in many instances, a well defined interface is not witnessed. The solid–liquid interface could be discrete and not continuous. Here process of feeding the solidification sites that witness considerable shrinkages, may become complicated. On grounds of above it is implied, the process of solidification constitutes an important aspects in the production of a defect free casting.",book:{id:"10432",slug:"casting-processes-and-modelling-of-metallic-materials",title:"Casting Processes and Modelling of Metallic Materials",fullTitle:"Casting Processes and Modelling of Metallic Materials"},signatures:"Upendra Kumar Mohanty and Hrushikesh Sarangi",authors:[{id:"328540",title:"Prof.",name:"Hrushikesh",middleName:null,surname:"Sarangi",slug:"hrushikesh-sarangi",fullName:"Hrushikesh Sarangi"},{id:"328543",title:"Prof.",name:"Upendra Kumar",middleName:null,surname:"Mohanty",slug:"upendra-kumar-mohanty",fullName:"Upendra Kumar Mohanty"}]},{id:"48856",title:"Silicon Carbide in Microsystem Technology — Thin Film Versus Bulk Material",slug:"silicon-carbide-in-microsystem-technology-thin-film-versus-bulk-material",totalDownloads:2887,totalCrossrefCites:4,totalDimensionsCites:10,abstract:"This chapter looks at the role of silicon carbide (SiC) in microsystem technology. It starts with an introduction into the wide bandgap (WBG) materials and the properties that make them potential candidates to enable the development of harsh environment microsystems. The future commercial success of WBG microsystems depends mainly on the availability of high-quality materials, well-established microfabrication processes, and economic viability. In such aspects SiC platform, in relation to other WBG materials, provides a clear and competitive advantage. The reasons for this will be detailed. Furthermore, the current status of the SiC thin film and bulk material technologies will also be discussed. Both SiC material forms have played important roles in different microsystem types.",book:{id:"4721",slug:"advanced-silicon-carbide-devices-and-processing",title:"Advanced Silicon Carbide Devices and Processing",fullTitle:"Advanced Silicon Carbide Devices and Processing"},signatures:"Mariana Amorim Fraga, Matteo Bosi and Marco Negri",authors:[{id:"9292",title:"Dr.",name:"matteo",middleName:null,surname:"bosi",slug:"matteo-bosi",fullName:"matteo bosi"},{id:"38456",title:"Dr.",name:"Mariana",middleName:null,surname:"Amorim Fraga",slug:"mariana-amorim-fraga",fullName:"Mariana Amorim Fraga"},{id:"175671",title:"MSc.",name:"Marco",middleName:null,surname:"Negri",slug:"marco-negri",fullName:"Marco Negri"}]},{id:"46237",title:"Corrosion Resistance Through the Application of Anti- Corrosion Coatings",slug:"corrosion-resistance-through-the-application-of-anti-corrosion-coatings",totalDownloads:7398,totalCrossrefCites:11,totalDimensionsCites:32,abstract:null,book:{id:"3817",slug:"developments-in-corrosion-protection",title:"Developments in Corrosion Protection",fullTitle:"Developments in Corrosion Protection"},signatures:"Api Popoola, OE Olorunniwo and OO Ige",authors:[{id:"169258",title:"Dr.",name:"Patricia",middleName:null,surname:"Popoola",slug:"patricia-popoola",fullName:"Patricia Popoola"}]},{id:"46235",title:"Corrosion Detection for Automated Visual Inspection",slug:"corrosion-detection-for-automated-visual-inspection",totalDownloads:3578,totalCrossrefCites:18,totalDimensionsCites:32,abstract:null,book:{id:"3817",slug:"developments-in-corrosion-protection",title:"Developments in Corrosion Protection",fullTitle:"Developments in Corrosion Protection"},signatures:"Francisco Bonnin-Pascual and Alberto Ortiz",authors:[{id:"124589",title:"Prof.",name:"Alberto",middleName:null,surname:"Ortiz",slug:"alberto-ortiz",fullName:"Alberto Ortiz"},{id:"169256",title:"Ph.D. Student",name:"Francisco",middleName:null,surname:"Bonnin-Pascual",slug:"francisco-bonnin-pascual",fullName:"Francisco Bonnin-Pascual"}]}],onlineFirstChaptersFilter:{topicId:"944",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"82118",title:"Surface Hardening of Stainless Steel",slug:"surface-hardening-of-stainless-steel",totalDownloads:24,totalDimensionsCites:0,doi:"10.5772/intechopen.105036",abstract:"The addition of nitrogen to stainless steel improves mechanical and corrosion properties. Nitrogen-bearing stainless steel (HNSS) is a new corrosion-resistant alloy class exhibiting better tribological properties. High-pressure and powder metallurgy techniques were developed for the fabrication of HNSS. Solid-state routes allow nitrogen introduction through thermochemical, implantation, or plasma surface treatments. High-temperature gas nitriding (HTGN), carried out in an N2 atmosphere in the 1000°C range, allows N uptake, obtaining thick, ~0.5–1.0 wt.% N austenitic cases. HTGN is different from conventional nitriding, performed in the 500°C range, where intense CrxNy precipitation occurs, impairing the corrosion resistance. Low-temperature plasma nitriding (LTPN) introduces more N in solution, and colossal supersaturated expanded phases (~45 at.%N) are formed. N supersaturation and compressive stresses increase the hardness of the surface layer to 10–14 GPa. Ferritic, martensitic, duplex, and precipitation-hardened stainless steels can be surface-treated by LTPN, obtaining expanded ferrite and martensite. However, single LTPN stainless steel may prematurely fail when submitted to high loading, as the thin and hard expanded layers collapse due to lack of load-bearing capacity. Duplex-nitriding treatment (HTGN + LTPN) results in a thick nitrogen-rich hardened austenite substrate layer, granting mechanical support and adhesion to the expanded austenite layer.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"André Paulo Tschiptschin and Carlos Eduardo Pinedo"},{id:"81579",title:"Welding Based Additive Manufacturing: Fundamentals",slug:"welding-based-additive-manufacturing-fundamentals",totalDownloads:34,totalDimensionsCites:0,doi:"10.5772/intechopen.104768",abstract:"Additive Manufacturing (AM) has drawn abundant attention over the past decades in the manufacturing and fabrication industries, especially to make part models and prototypes. This chapter introduces a potential welding based AM process called Wire Arc Additive Manufacturing (WAAM) for the fabrication of near-net shaped metal components including stainless steel components. To start with traditional AM processes, various fundamental traditional AM for the fabrication of components have been presented. Wire Arc Additive Manufacturing (WAAM) has been explained with its variants, synonyms, different welding processes to suit WAAM particularly to weld stainless steel metal; primary process selections for working with WAAM, important metals, and alloys that could be used in WAAM have been elaborated. A case study for WAAM fabrication of AISI 316 L stainless steel plate is included to introduce the fabrication of metal components using WAAM. Further, the most common defects which possibly play a vital role in WAAM components fabrication and a few of the future challenges regarding WAAM development are discussed. Fundamental information covered in this chapter could be more beneficial to beginners for the understanding of WAAM process generally including stainless steel component fabrication in a lucid tactic.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"Maruthasalam Sowrirajan, Selvaraj Vijayan and Munusamy Arulraj"},{id:"80664",title:"Dependence of Corrosion Resistance of Austenitic Chromium-Nickel Steels on the Magnetic State of Austenite",slug:"dependence-of-corrosion-resistance-of-austenitic-chromium-nickel-steels-on-the-magnetic-state-of-aus",totalDownloads:59,totalDimensionsCites:0,doi:"10.5772/intechopen.102388",abstract:"Corrosive behavior of austenitic chromium-nickel steels from the magnetic state (parameter χ0) of austenite, pre-formed to interact with aggressive media are research. Correlation between the rate K of pitting corrosion and the specific magnetic susceptibility χ0 of austenite was experimentally established. It is experimentally established that the corrosion resistance of austenitic steels AISI304, 08Cr18Ni10, AISI 321, 08Cr18Ni10Тi (containing a low amount of δ-ferrite ∼0.005…0.5%) depends on the magnetic state of austenite: the corrosion rate of steel decreases with increases χ0 austenite. The tendency of change in the corrosion rate of austenitic alloy with a high nickel content 06Crh28NiMoCuTi (not contain δ-ferrite) has the opposite character: with increasing χ0, the corrosion rate of the alloy increases is revealed. For austenitic chromium-nickel steels, the corrosion rates of the individual (austenite (A), δ-ferrite (F), strain-induced α′-martensite (M)) and total (A + F, A + M and A + F + M) phases are determined. It is proposed to predict corrosion according to the specific magnetic susceptibility χ0 of austenite and the amount δ-ferrite.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"Gennadii Snizhnoi"},{id:"80199",title:"The Evaluation of the Comparative Corrosion Behaviour of Conventional and Low-Nickel Austenitic Stainless Steel: Hercules™ Alloy",slug:"the-evaluation-of-the-comparative-corrosion-behaviour-of-conventional-and-low-nickel-austenitic-stai",totalDownloads:56,totalDimensionsCites:0,doi:"10.5772/intechopen.102381",abstract:"Austenitic stainless steels require approximately 8% Ni to maintain austenitic microstructure at room temperature for alloys such as 304 stainless steel (304SS). Ni contributes approximately 60% of the total material cost and its price fluctuates, making the cost of austenitic stainless steel unpredictable. The use of low-nickel austenitic stainless steels as a substitute has been considered in order to remedy costs associated with Ni price fluctuations. Alloying elements such as Mn and N have been considered, however they have been found to reduce corrosion resistance. A new alloy namely Hercules™ has been developed with reduced Ni content (1.8–2% Ni). This chapter presents a comparative study of the corrosion behavior of Hercules™ and 304SS in different solutions. The alloys were evaluated using cyclic polarisation technique and immersion tests. The results demonstrated that the corrosion resistance of Hercules™ is comparable to that of 304SS. This presents the alloys as potential industrial substitutes of each other.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"Duduzile Nkomo and Nomsombuluko Masia"},{id:"80346",title:"Nitrogen Supersaturation of AISI316 Base Stainless Steels at 673 K and 623 K for Hardening and Microstructure Control",slug:"nitrogen-supersaturation-of-aisi316-base-stainless-steels-at-673-k-and-623-k-for-hardening-and-micro",totalDownloads:59,totalDimensionsCites:1,doi:"10.5772/intechopen.102387",abstract:"The high-density plasma nitriding at 673 K and 623 K was employed to make 10% of nitrogen supersaturation on AISI316 base austenitic stainless steels. The processing parameters and nitrogen-hydrogen gas flow ratio were optimized to increase the yield of N2+ ion and NH-radical for efficient nitriding. The nitrided AISI316 specimens were prepared for multidimensional analysis to describe the fundamental features of low-temperature plasma nitriding. First, macroscopic evaluation revealed that nitrogen supersaturation induced the γ-lattice expansion and the higher nitrogen content than 4% of mass in depth. The mesoscopic analysis describes the holding temperature and initial grain-size effects on the microstructure changes. Plastic straining, grain-size refinement, and nitrogen zone-boundary diffusion processes advance with nitrogen supersaturation to drive the inner nitriding behavior. The microscopic analysis explains the microstructure refinement, the two-phase structuring, and the microstructure modification. Through this multi-dimensional analysis, the essential characteristics of the low-temperature plasma nitriding of 316 austenitic stainless steels were precisely understood to extend the engineering treatise on the bulk nitrogen stainless steels for surface modification and treatment of stainless steels by nitriding. This plasma nitriding was applied to strengthen and harden the AISI316 wire surfaces toward its application on surgery wires.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"Tatsuhiko Aizawa, Tomomi Shiratori, Tomoaki Yoshino, Yohei Suzuki and Takafumi Komatsu"},{id:"79904",title:"Corrosion Resistance, Evaluation Methods, and Surface Treatments of Stainless Steels",slug:"corrosion-resistance-evaluation-methods-and-surface-treatments-of-stainless-steels",totalDownloads:106,totalDimensionsCites:1,doi:"10.5772/intechopen.101430",abstract:"Stainless steels are widely recognized and find applications in many engineering industries and companies due to their excellent properties including high resistance to corrosion as a result of their minimum 10.5% chromium content, exceptional strength and durability, temperature resistance, high recyclability, and easy formability. In the present book chapter, the basic concepts of stainless steel including its applications, classifications, and corrosion properties will first be discussed. Thereafter, their corrosion behaviour will then be explained. 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That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:null,institution:null},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"417317",title:"Mrs.",name:"Chiedza",middleName:null,surname:"Elvina Mashiri",slug:"chiedza-elvina-mashiri",fullName:"Chiedza Elvina Mashiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"352140",title:"Dr.",name:"Edina",middleName:null,surname:"Chandiwana",slug:"edina-chandiwana",fullName:"Edina Chandiwana",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"342259",title:"B.Sc.",name:"Leonard",middleName:null,surname:"Mushunje",slug:"leonard-mushunje",fullName:"Leonard Mushunje",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"347042",title:"Mr.",name:"Maxwell",middleName:null,surname:"Mashasha",slug:"maxwell-mashasha",fullName:"Maxwell Mashasha",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"2941",title:"Dr.",name:"Alberto J.",middleName:"Jorge",surname:"Rosales-Silva",slug:"alberto-j.-rosales-silva",fullName:"Alberto J. Rosales-Silva",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"437913",title:"Dr.",name:"Guillermo",middleName:null,surname:"Urriolagoitia-Sosa",slug:"guillermo-urriolagoitia-sosa",fullName:"Guillermo Urriolagoitia-Sosa",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"435126",title:"Prof.",name:"Joaquim",middleName:null,surname:"José de Castro Ferreira",slug:"joaquim-jose-de-castro-ferreira",fullName:"Joaquim José de Castro Ferreira",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"437899",title:"MSc.",name:"Miguel Angel",middleName:null,surname:"Ángel Castillo-Martínez",slug:"miguel-angel-angel-castillo-martinez",fullName:"Miguel Angel Ángel Castillo-Martínez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"289955",title:"Dr.",name:"Raja",middleName:null,surname:"Kishor Duggirala",slug:"raja-kishor-duggirala",fullName:"Raja Kishor Duggirala",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jawaharlal Nehru Technological University, Hyderabad",country:{name:"India"}}}]}},subseries:{item:{id:"3",type:"subseries",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"\r\n\tThe integration of tissues and organs throughout the mammalian body, as well as the expression, structure, and function of molecular and cellular components, is essential for modern physiology. The following concerns will be addressed in this Cell Physiology subject, which will consider all organ systems (e.g., brain, heart, lung, liver; gut, kidney, eye) and their interactions: (1) Neurodevelopment and Neurodevelopmental Disease (2) Free Radicals (3) Tumor Metastasis (4) Antioxidants (5) Essential Fatty Acids (6) Melatonin and (7) Lipid Peroxidation Products and Aging Physiology.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/11.jpg",keywords:"Neurodevelopment and Neurodevelopmental Disease, Free Radicals, Tumor Metastasis, Antioxidants, Essential Fatty Acids, Melatonin, Lipid Peroxidation Products and Aging Physiology"},{id:"12",title:"Human Physiology",scope:"Human physiology is the scientific exploration of the various functions (physical, biochemical, and mechanical properties) of humans, their organs, and their constituent cells. The endocrine and nervous systems play important roles in maintaining homeostasis in the human body. Integration, which is the biological basis of physiology, is achieved through communication between the many overlapping functions of the human body's systems, which takes place through electrical and chemical means. Much of the basis of our knowledge of human physiology has been provided by animal experiments. Because of the close relationship between structure and function, studies in human physiology and anatomy seek to understand the mechanisms that help the human body function. The series on human physiology deals with the various mechanisms of interaction between the various organs, nerves, and cells in the human body.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/12.jpg",keywords:"Anatomy, Cells, Organs, Systems, Homeostasis, Functions"},{id:"13",title:"Plant Physiology",scope:"Plant Physiology explores fundamental processes in plants, and it includes subtopics such as plant nutrition, plant hormone, photosynthesis, respiration, and plant stress. In recent years, emerging technologies such as multi-omics, high-throughput technologies, and genome editing tools could assist plant physiologists in unraveling molecular mechanisms in specific critical pathways. The global picture of physiological processes in plants needs to be investigated continually to increase our knowledge, and the resulting technologies will benefit sustainable agriculture.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/13.jpg",keywords:"Plant Nutrition, Plant Hormone, Photosynthesis, Respiration, Plant Stress, Multi-omics, High-throughput Technology, Genome Editing"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:null,selectedSubseries:null},seriesLanding:{item:{id:"6",title:"Infectious Diseases",doi:"10.5772/intechopen.71852",issn:"2631-6188",scope:"This series will provide a comprehensive overview of recent research trends in various Infectious Diseases (as per the most recent Baltimore classification). Topics will include general overviews of infections, immunopathology, diagnosis, treatment, epidemiology, etiology, and current clinical recommendations for managing infectious diseases. Ongoing issues, recent advances, and future diagnostic approaches and therapeutic strategies will also be discussed. This book series will focus on various aspects and properties of infectious diseases whose deep understanding is essential for safeguarding the human race from losing resources and economies due to pathogens.",coverUrl:"https://cdn.intechopen.com/series/covers/6.jpg",latestPublicationDate:"August 16th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:124,numberOfPublishedBooks:13,editor:{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",fullName:"Alfonso J. Rodriguez-Morales",profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},subseries:[{id:"3",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"