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  Table of Contents    
ORIGINAL ARTICLE  
Year : 2019  |  Volume : 62  |  Issue : 4  |  Page : 529-536
Omics data-driven analysis identifies laminin-integrin-mediated signaling pathway as a determinant for cell differentiation in oral squamous cell carcinoma


1 Department of Oral Pathology and Microbiology, Manipal College of Dental Sciences, Manipal Academy of Higher Education, Manipal, India
2 Department of Oral Pathology and Microbiology, Yenepoya Dental College, Yenepoya (Deemed to be University), Mangalore, India
3 Center for Systems Biology and Molecular Medicine Yenepoya (Deemed to be University), Mangalore, India

Click here for correspondence address and email

Date of Web Publication14-Oct-2019
 

   Abstract 


Background: In recent years, high-throughput omics technologies have been widely used globally to identify potential biomarkers and therapeutic targets in various cancers. However, apart from large consortiums such as The Cancer Genome Atlas, limited attempts have been made to mine existing datasets pertaining to cancers. Methods and Results: In the current study, we used an omics data analysis approach wherein publicly available protein expression data were integrated to identify functionally important proteins that revealed consistent dysregulated expression in head and neck squamous cell carcinomas. Our analysis revealed members of the integrin family of proteins to be consistently altered in expression across disparate datasets. Additionally, through association evidence and network analysis, we also identified members of the laminin family to be significantly altered in head and neck cancers. Members of both integrin and laminin families are known to be involved in cell-extracellular matrix adhesion and have been implicated in tumor metastatic processes in several cancers. To this end, we carried out immunohistochemical analyses to validate the findings in a cohort (n = 50) of oral cancer cases. Laminin-111 expression (composed of LAMA1, LAMB1, and LAMC1) was found to correlate with cell differentiation in oral cancer, showing a gradual decrease from well differentiated to poorly differentiated cases. Conclusion: This study serves as a proof-of-principle for the mining of multiple omics datasets coupled with selection of functionally important group of molecules to provide novel insights into tumorigenesis and cancer progression.

Keywords: Differentiation, extracellular matrix, immunohistochemistry, integrin, laminin, omics

How to cite this article:
Kulkarni S, Abdulla R, Jose M, Adyanthaya S, B Rex D A, Patil AH, Pinto SM, Subbannayya Y. Omics data-driven analysis identifies laminin-integrin-mediated signaling pathway as a determinant for cell differentiation in oral squamous cell carcinoma. Indian J Pathol Microbiol 2019;62:529-36

How to cite this URL:
Kulkarni S, Abdulla R, Jose M, Adyanthaya S, B Rex D A, Patil AH, Pinto SM, Subbannayya Y. Omics data-driven analysis identifies laminin-integrin-mediated signaling pathway as a determinant for cell differentiation in oral squamous cell carcinoma. Indian J Pathol Microbiol [serial online] 2019 [cited 2019 Nov 15];62:529-36. Available from: http://www.ijpmonline.org/text.asp?2019/62/4/529/269055





   Introduction Top


Oral cancer is a growing health risk across the world. According to Global cancer statistics,[1] cancers of the lip and the oral cavity constituted the eighth most leading cancers in 2012.[2] In 2017, the number of projected cases of head and neck cancer in the United States alone accounted for an estimated 50,000 new cases and 9700 mortalities.[3] Most cases of head and neck cancers present at an advanced stage and only about a third present with early stage disease.[4] The 5-year survival in advanced stages is about 50% and this scenario has not improved since decades.[5] However, it has been reported that despite therapy, up to 60% of the patients develop locoregional recurrence while about 30% develop distant recurrence.[6] This necessitates the identification of biomarkers for screening and prognosis of head and neck cancers. Analysis of existing “omics” datasets on head and neck cancers can help in the identification of signaling modules linked to tumor progression, therapy, and prognosis.

Over the years, there has been an increase in high-throughput multiomics datasets on head and neck cancers. This has led to the identification of several biologically important genes and signaling networks that are frequently reported to be dysregulated in head and neck as well as other cancers. Furthermore, integrated approaches such as proteogenomics are also revolutionizing the discovery of biomarkers and therapeutic targets in cancers.[7] Several groups around the world including “The Cancer Genome Atlas” (TCGA) and “The Clinical Proteomic Tumor Analysis Consortium” (CPTAC) have carried out genomics, transcriptomic, and proteomic analysis of various cancers and made these datasets publicly available to the scientific community. Currently, integrated analysis of several cancers, including breast,[8] bladder,[9] cervical,[10] colorectal,[11] endometrial,[12] esophageal,[13] gastric,[14] lung,[9] and ovarian cancers,[15] has been carried out. However, in the case of oral cancers, studies involving mining of existing omics datasets are limited. There have been a series of research articles published from India and elsewhere pertaining to the proteome expression profile of these cancers.[16],[17],[18],[19] Studying the proteome profile is imperative as it represents an important complement to genomics in showing which genes are actually expressed.[20] Attempts to integrate the data from different platforms to analyze and identify proteins that are commonly dysregulated across these studies will enable selection of functionally important group of molecules that can provide novel insights into tumorigenesis and cancer progression.

In this study, we used a bioinformatics approach to integrate data from previous studies on head and neck cancers to identify potential biomarkers. Our analysis revealed members of the integrin family of proteins to be consistently altered in expression across disparate datasets. Additionally, through association evidence and network analysis, we identified members of the laminin family to be significantly altered in oral cancers. To confirm the validity of our findings, we carried out immunohistochemical analysis of the laminin gene family members in confirmed oral cancer cases. This proof-of-principle study emphasizes the need for similar studies that will enable mining of multiple omics datasets coupled with selection of functionally important group of molecules to provide novel insights into tumorigenesis and cancer progression. Mining omics datasets will provide a broader image of molecular mechanisms in various cancers.


   Materials and Methods Top


Bioinformatics analysis

Literature survey was carried out to identify previously published high-throughput datasets on oral squamous cell carcinoma (OSCC). The keywords “head and neck squamous cell cancers” and “proteomics” were used for the literature mining. The available literature was manually screened to identify high-throughput studies on head-and-neck cancers involving comparison between normal and tumor cell lines. We identified two studies that matched our criteria.[18],[20] We obtained the differential expression of the proteins from the publicly available supplementary data and identified that the classes of integrins were predominantly downregulated in these studies. Besides, these classes of proteins were not described in detail by these articles. Network analysis of differentially expressed integrins in head and neck squamous cell carcinoma (HNSCC) was carried out using STRING (http://string-db.org/).[21] The parameters used for the STRING analysis included interaction sources from databases, co-expression, neighborhood, and co-occurrence. The network generation used 20 interactors in the first shell and no more than five interactors in the second shell.

The list of differentially expressed integrins from head-and-neck cancer datasets was used to carry out the pathway analysis. Pathway analysis was carried out using KEGG database through DAVID 6.8 (https://david.ncifcrf.gov).[22] The most enriched pathways were used for further analysis. A network analysis was carried out with Cytoscape 3.5.0 to assess the association of integrins and laminins with epithelial–mesenchymal transition (EMT) markers in the combined head and neck cancer dataset.[23] Known markers of EMT and members of the laminin and integrin family were used to generate the network.

Formalin-fixed paraffin-embedded (FFPE) blocks

Archival FFPE sections were obtained for 50 histologically diagnosed cases of OSCC. The study used two groups consisting of 25 cases each of OSCC from patients <45 years and ≥45 years. The 50 cases consisted of 30 cases of well-differentiated SCC and 20 cases of poorly differentiated SCC that were equally distributed across both the groups. Skin tissue was used as control. The FFPE blocks were sectioned using a semi-automated microtome and subjected to immunohistochemical analysis.

Histopathological evaluation

The paraffin-embedded tissue blocks were retrieved from the archives. The sections were inspected to confirm the adequate size of the tissue. The slides were graded and selected according to modified Broders' system and 30 slides of well-differentiated SCC and 20 slides of poorly differentiated SCC were obtained. The selected slides were then coded to remove bias during the evaluation. From each selected case, two serial sections of five microns each were prepared. One section was stained with hematoxylin and eosin (H and E) and the other by immunostaining method. All the slides were methodically evaluated by two different observers in order to remove inter- and intra-observer bias.

Immunohistochemistry

FFPE wax blocks were used to obtain 5 μm tissue sections for immunostaining. The cut sections were then mounted on to poly-l-lysine-coated slides and incubated at a temperature of 55–60°C. The tissue sections were deparaffinized using three changes of xylene for 10 min each. The sections were then rehydrated using decreasing concentrations of ethanol and subjected to enzymatic antigen retrieval using pepsin solution. Briefly, the slides were immersed in preheated distilled water for 15 min at 37°C and treated with the pepsin solution (pH 2–2.5) for 15 min at 37°C. The slides were then rinsed in water and blotted gently. Endogenous peroxidases were quenched by treating the sections with peroxide block solution (BioGenex) for 10 min. The slides were then rinsed in distilled water for 2 min followed by two washes with Tris–buffer saline (Tris salt 6.5 g + sodium chloride 8.5 g + 4 ml of concentrated HCl + 1 l distilled water, pH 7.4–7.6) for 3 min each. The slides were treated with Power Block (BioGenex) for 10 min to prevent non-specific binding of secondary antibody. The sections were incubated with rabbit polyclonal laminin antibody (Catalog # U078-UP, BioGenex) for 90 min at room temperature in a moist chamber. The sections were then rinsed twice in wash buffer for 5 min, and treated with Super Enhancer (BioGenex) for 20 min. The sections were then treated with SS Label reagent (SS polymer HRP, BioGenex) for 30 min. The solution comprised of secondary antibody conjugated to nonbiotinylated polymer HRP reagent. The slides were rinsed twice in wash buffer and incubated with substrate solution (3, 3'-diaminobenzidine tetrahydrochloride, DAB buffer, and DAB chromogen) for 5 min. The slides were then rinsed with distilled water to remove the excess DAB, counterstained with Mayer's hematoxylin, dehydrated, and mounted with xylene-based medium. The immunohistochemical labeling was assessed by an experienced pathologist.

Interpretation of staining

The slides were viewed in a bright field microscope at a magnification of 10× to analyze the intensity and integrity pattern of staining. A positive laminin expression was designated for samples showing basement membrane staining. Erythrocytes present in every section served as an internal positive control. All the slides were methodically evaluated by two different observers in order to remove the inter- and intra-observer bias. On light microscopic examination a brown reaction product was seen surrounding tumor islands, consistent with basement membrane retention or synthesis. Assessment of laminin staining pattern was done around the tumor islands, cords, and individual dysplastic epithelial cells by attributing the presence or absence and the continuity of laminin as a parameter for the study. The semi-quantitative analysis of the stained sections was done by light microscopy and the grading of the intensity and integrity of laminin expression in the basal membrane was carried out as per previous studies.[24],[25]


   Results and Discussion Top


Dysregulated integrin–laminin signaling in head and neck cancers

We carried out a detailed bioinformatics analysis of proteomics datasets of oral cancer to identify signaling pathways aberrant in oral cancer. Literature mining revealed two high-throughput studies on head and neck cancers involving comparison between normal and tumor lines.[17],[19] The study by Syed et al.used an iTRAQ-based proteomics approach to compare the proteomic profiles of a panel of HNSCC cell lines with a non-neoplastic oral keratinocyte cell line. This study led to the identification of 375 proteins that were differentially expressed in at least two of the three HNSCC cell lines.[19] Interestingly, we observed the downregulation of six members of the integrin family, including ITGA2, ITGA3, ITGA5, ITGA6, ITGAV, and ITGB1. A subsequent study by Radhakrishnan et al. used a tandem mass tag-based quantitative proteomic approach to identify signaling alterations across a panel of HNSCC cell lines.[17] This led to the identification of 1128 differentially expressed proteins. In concurrence with our findings from Syed et al., we also observed downregulation of seven members of the integrin family including ITGA3, ITGB8, ITGB1, ITGB4, ITGA2, ITGA6, and ITGAV in HNSCC cell lines in comparison to normal keratinocyte cell line. Put together, our analysis revealed association of members of the integrin family with cancer tumorigenesis.

In order to identify interacting partners as associated networks, we next combined the differentially expressed integrins identified from these two studies and carried out Network analysis using STRING (http://string-db.org). Our analysis revealed members of the laminin family, including LAMB1, LAMB2, LAMB3, LAMA2, and LAMC2 to be associated using members of the integrin family [Figure 1]. In order to identify the pathways that are dysregulated as a result of decreased expression of integrins as identified in the proteomic studies, we performed pathway-enrichment analysis using DAVID. Our results indicate the enrichment of extracellular matrix (ECM)-receptor interaction pathway in head and neck cancer [Figure 2], thereby corroborating the results from previous studies. The ECM is an important component of the tumor microenvironment and acts as a key barrier to tumor cell extravasation and invasion.[26]
Figure 1: Network analysis of differentially expressed integrins in head and neck cancers. The list of differentially expressed integrins from previously published proteomics data was used as input for STRING to carry out network analysis. The analysis revealed that a few members of the laminin family were found to be associated with members of the integrin family

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Figure 2: Role of integrins in the ECM-receptor interaction pathway. The list of differentially expressed integrins was used to carry out pathway analysis using KEGG through DAVID. The results indicated the enrichment of ECM-receptor pathway in head and neck cancer cell lines. The various members of the integrin family along with their expression are depicted in the pathway

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Role of integrins and laminins in cancer progression

The integrin family of cell surface receptors mediate the process of adhesion to ECM and immunoglobulins.[27] They are heterodimers comprising alpha and beta subunits, forming at least 24 distinct combinations.[28] The extent of cell adhesion and migration often depends on the repertoire of integrins expressed on the cell surface of a specific cell type.[29] The role of integrins in cell migration and tumor invasion is well understood. Cancer cells have been reported to facilitate their invasion through the selective expression of integrins that bind to stromal constituents generated by extracellular proteases.[30] Invasive and metastatic cells are also known to exhibit changes in their integrin expression profile.[31] Integrins have also been known to work cooperatively with oncogenes, growth factor receptors, and cytokine receptors to drive tumorigenesis and tumor progression.[29] These studies suggest their potential as drug targets to significantly reduce tumor burden. Several preclinical studies have validated the therapeutic potential of integrins.[32],[33],[34]

Recently, a TCGA dataset containing genomic and transcriptomic data from 235 head and neck cancer patients was analyzed to compare tumor gene expression across progressor and nonprogressor groups.[35] Analysis of the identified differentially expressed genes indicated the dysregulation of the integrin signaling pathway and its association with the process of tumor progression. Further, ITGB3 expression was found to be 36-fold higher in cancer stem-like cells isolated from HNSCC cells as compared to parental cells.[36] Integrin expression levels have also been found to correlate with metastasis and prognosis of OSCC. Patients with higher expression levels of the integrins—ITGA3, ITGA6, and ITGB1—were found to have better prognosis.[37]

Laminins form an important class-binding partners of integrins. Laminins are a family of glycoproteins that interact with receptors of cells adjacent to the basement membranes and thereby maintain the structural integrity and physiology of basement membranes.[38] This family consists of 12 genes encoding for alpha, beta, and gamma chains that form 18 heterotrimeric associations among them.[39] Laminins play an important role in cell–ECM interactions.[40] The role of laminins in cell migration and adhesion in normal and tumor cells is well established. Their involvement in invasion and metastatic processes of tumor cells has also been demonstrated.[41] It has also been suggested that dysregulated laminin expression may aid cancer stem cells in maintaining their phenotype.[41] In a previous study, a laminin-111 fragment generated by matrix metalloproteinase-2 was found to play a role in stem cell differentiation through α3β1 integrin-mediated regulation of EMT.[42]

Loss of laminin anchoring has been shown to be a feature of aggressive astrocytomas and has been associated with poor prognosis.[43] Earlier, melanoma cells have been reported to express multiple laminin isoforms and migrate strongly through α5-laminin activity mediated by integrin receptors.[44] In fact, restoring/increasing laminin expression has been proven to be beneficial in transforming tumor cells to a “normal” phenotype. Human breast cancer cells cultured in 3D basement membranes enriched with laminin have been previously shown to transform to a “near normal phenotype.”[45] Further, it was found that addition of laminin-111 to epithelial cells led to quiescence through a mechanism involving nuclear beta-actin [46] and exportin-6.[47] In addition, members of the laminin family can potentially serve as candidate diagnostic markers. In a previous study on the salivary proteome, six members of the laminin family, including LAMA3, LAMA4, LAMB2, LAMC1, LAMC2, and LAMC3, were identified.[48] Indicating its potential utility as a marker of cell differentiation.

Role of laminins and integrins in EMT

EMT allows an epithelial cell normally in contact with the basement membrane to undergo a series of biochemical changes and assume a mesenchymal cell phenotype.[49] The EMT confers the cell with enhanced capabilities, including increased migratory capacity, increased invasiveness, resistance to apoptotic mechanisms, and increased production of components of the extracellular matrix. EMT aids in tumorigenesis by enhancing the migration and invasion of cancer cells.[50] EMT, therefore, can result in local invasion of tumor cells or metastasis.[51] Both integrins and laminins are known to be associated with the process of EMT in various cancer.[52],[53],[54] In order to analyze the association between the members of laminin and integrins in head and neck cancers, we compiled lists of known epithelial and mesenchymal markers and members of the integrin and laminin family from literature and carried out a network analysis using Cytoscape [Figure 3]. We also analyzed the expression of these proteins in the compiled HNSCC dataset. We identified 15 of the 27 epithelial markers and 9 of the 20 mesenchymal markers. Of the epithelial markers, we observed the downregulation of Claudin-1 (CLDN1), Cytokeratin 14 (KRT14), Cytokeratin 19 (KRT19), Laminin-1 (LAMC1) and Desmoglein-3 (DSG3) and the upregulation of epithelial cell adhesion molecule across all head and neck cancer cell lines. Of the mesenchymal markers, Fibronectin (FN1), Integrin β1/CD29 (ITGB1), Laminin α3/Laminin-5 (LAMA3), Tenascin C (TNC), Vimentin (VIM), and transforming growth factor beta 1 (TGFB1) were downregulated while Vitronectin (VTN) 1 protein was upregulated across head and neck cancer cells. These data suggest that the cell lines have a mixed phenotype. We identified 8 of the 33 integrin family members and 6 of 12 laminin family members to be differentially expressed in head and neck cancers. Members of the integrin and laminin family were found to be associated with EMT markers through a network suggesting their involvement in cell differentiation.
Figure 3: Association of members of the integrin and laminin family with EMT in HNSCC. (a) A schematic depicting EMT in cancers. (b) Integrated network depicting interactions of EMT markers with integrin and laminin family members. The expression of EMT markers identified in previous HNSCC studies has been depicted in the legend

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Immunohistochemical validation of laminin

The association of laminins with the ECM-receptor interaction pathway and other findings put together suggested the correlation of laminin expression with tumor differentiation. We further validated laminin-111 expression in oral cancers in various stages of differentiation using immunohistochemistry. The staining intensity and integrity of basal membrane laminin was graded as per criteria provided in [Table 1].
Table 1: Parameters for intensity grading and integrity of basal membrane laminin

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Grading of intensity

Subsequent to immunohistochemical validation, the slides were evaluated for their staining intensity. On evaluating laminin immunostaining pattern, in case of well-differentiated SCC (30 cases), 12 (40%) cases showed intense (+++) staining, 7 (23.3%) cases showed moderate (++) staining, 6 (20%) cases showed discrete (+) intensity, and 5 (16.6%) cases showed complete absence (–) of staining [Table 2]. In case of poorly differentiated SCC (20 cases), 2 (10%) cases showed intense (+++) staining, 6 (30%) cases showed moderate (++) intensity, 10 (50%) cases showed discrete (+) staining, and 2 (10%) cases showed complete absence (–) of staining. Comparing the intensity grading between well-differentiated SCC and poorly differentiated SCC using Fisher's exact t-test, the P value was significant (P value = 0.040). In our study it was found that the predominant grade of staining was intense (40%) in well-differentiated SCC, whereas in poorly differentiated SCC it was discrete (32.0%) pattern.
Table 2: Comparison of intensity grading and integrity of basal membrane laminin between well-differentiated OSCC and poorly differentiated SCC

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Grading of integrity

The slides were further evaluated for the staining pattern. On analyzing the integrity (continuity) pattern, in case of well-differentiated SCC (30 cases), 8 (26.7%) cases showed continuous pattern of staining, 9 (30%) cases showed moderately continuous pattern, 7 (23.3%) cases showed discretely continuous pattern, and complete absence or compete loss of integrity was observed in 6 (20.0%) cases [Table 2]. In poorly differentiated SCC, out of 20 cases, considering the integrity, continuous (+++) pattern was completely absent, moderately continuous pattern was seen in 4 (20%) cases, 13 (43.3%) cases showed discretely continuous pattern, and complete absence of integrity was seen in 3 (15%) cases. Comparing the integrity grading between well-differentiated SCC and poorly differentiated SCC using Fisher's exact t-test, the P value was highly significant (P-value = 0.003). In case of well-differentiated SCC laminin expression was predominantly moderate continuous (30.0%), whereas in poorly differentiated SCC it is predominantly discrete continuous (20%). There was no significant difference (Fisher's t-test, nonsignificant) observed when comparison was done between age groups (above and below 45 years) in well-differentiated and poorly differentiated SCC [Figure 4].
Figure 4: Immunohistochemical validation of laminin-111 expression in well and poorly differentiated OSCCs. (a) External positive control. (b) Internal positive control. (c) Photomicrograph showing intense staining around the tumor islands in well-differentiated SCC (40×). (d)Photomicrograph of laminin expression in poorly differentiated SCC (loss of integrity around the tumor islands) (20×)

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Our results are in accordance with the studies conducted by Tosios et al. where loss of continuity and epithelial basement membrane is associated with the invasive nature of SCC.[55] The basement membrane is ubiquitous extracellular structure consisting of collagenous and noncollagenous protein. The components of basal membrane act as a barrier against neoplastic invasion in SCCs, thus avoiding tumor cell dissemination.[56],[57] Laminin is a basement membrane glycoprotein that functions as an adhesive glycoprotein binding epithelial cell to Type IV collagen and basement membrane.[58],[59] It is distributed exclusively on the epithelial portion of basement membrane in the lamina lucida. Tumor cells bind to laminin receptors on the basal membrane and are subsequently stimulated to produce metalloproteinase, which begins fragmentation and degradation of the membrane.[60] Immunohistochemical studies of basal membrane components may be related to tumor invasion and have been shown to be effective in diagnosing and establishing the prognosis of cancer.

Laminin 332 (previously known as laminin 5) promotes tumorigenesis, especially in SCC through the interactions with several cell-surface receptors (including alpha6 beta4 and alpha3 beta1 integrins, epidermal growth factor receptor, and syndecan 1) and other basement membrane components (including Type VII collagen), and drives tumorigenesis through phosphatidylinositol-3 kinase (PI3K) and RAC1 activation, promoting tumor invasion and cell survival. The extracellular interactions of laminin 332 appear amenable to antibody-mediated therapies.[61] Although many invasive tumors lack extracellular immunoreactivity for laminin, some invasive tumors particularly the SCC exhibit focal extracellular immunoreactivity for laminin. Studies have shown the differences between the intensity and integrity of laminin expression in different grades of OSCC. There is gradual decrease in the expression of laminin from well-differentiated SCC to poorly differentiated SCC, suggesting that laminin-111 plays a role in cell differentiation.


   Conclusions Top


Analysis of “big data” from revolutionary technologies such as next-generation sequencing, proteomics, and metabolomics can potentially lead to the identification of novel biological insights. The sheer volume of data pertaining to diseases such as cancer that is generated every year suggests that there is ample scope for carrying out research without the need to generate new data. This “data deluge” has led several researchers to explore omics data using bioinformatics approaches.[62] In the current study, we used a bioinformatics approach to integrate data from previous studies on head and neck cancers and identified integrin and laminin family members to correlate with the cell differentiation state in cell line models and archival samples. This study serves as a proof-of-principle for the need for exploring existing omics datasets and identifying molecular mechanisms of diseases. However, this also brings about with it several challenges including normalization of disparate datasets, infrastructure for storage among others. Nevertheless, reanalysis of cancer omics datasets could reshape the ways we think about research and divert scarce resources from rediscovery to validation.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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Correspondence Address:
Yashwanth Subbannayya
Center for Systems Biology and Molecular Medicine Yenepoya (Deemed to be University), Mangalore - 575 018
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/IJPM.IJPM_1_19

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