Publications by authors named "Seema Khadirnaikar"

Cancer is a heterogeneous disease, and patients with tumors from different organs can share similar epigenetic and genetic alterations. Therefore, it is crucial to identify the novel subgroups of patients with similar molecular characteristics. It is possible to propose a better treatment strategy when the heterogeneity of the patient is accounted for during subgroup identification, irrespective of the tissue of origin.

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Non-small Cell Lung Cancer (NSCLC) is a heterogeneous disease with a poor prognosis. Identifying novel subtypes in cancer can help classify patients with similar molecular and clinical phenotypes. This work proposes an end-to-end pipeline for subgroup identification in NSCLC.

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The epithelial to mesenchymal transition (EMT) is crucial for cancer progression and chemoresistance. EMT is a dynamic process with multiple phases that change cell migration and invasion activity. We used pan-cancer expression data to find 14-LncRNAs that had a high correlation with the EMT markers VIM, CDH1, FN1, SNAI1, and SNAI2.

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Background: An increasing number of studies are indicating that the stemness phenotype is a critical determinant of the Lung adenocarcinoma (LUAD) patient's response. Thus, it is crucial to identify novel biomarkers for stemness determination.

Objective: Here, we aim to develop a robust LncRNAs based prognostic signature with a stemness association for the LUAD patients.

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Lung adenocarcinoma (LUAD) is a major health problem and has poor prognosis. Heterogeneity is a central determinant of the treatment outcome, requiring identification of new subclasses of LUAD. Senescence has emerged as a crucial regulator of metastasis and drug response.

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Background: Leukocyte infiltration plays an critical role in outcome of various diseases including Lung adenocarcinoma (LUAD).

Objectives: To understand the genetic and epigenetic factors affecting leukocyte infiltration and identification and validation of immune based biomarkers.

Method: Correlation analysis was done to get the associations of the factors.

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Cancer stem cells play an essential role in therapy response and aggressiveness of various cancers, including lung adenocarcinoma (LUAD). Interestingly it also shares many features of embryonic stem cells (ESCs). Recently, long non-coding RNAs (lncRNAs) have emerged as a critical regulator of cell physiology.

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Sequencing analysis finds many applications in various fields of biology from comparative genomics to clinical research. Recent studies, using high-throughput sequencing method, has generated terabytes of data. It is challenging to interpret and draw a meaningful conclusion without the proper understanding of various steps involved in the analysis of such data.

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Background: Ovarian cancer (OC) causes a significant proportion of cancer-related deaths in women. Recently, immunotherapy has emerged as a substantial player in cancer treatment. Lymphocyte infiltration, an important indicator of immune activity and disease aggressiveness, can be identified by gene expression profiling of immune-related genes of tumours which may prove useful in prognosis of patients.

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The prognostic signatures play an essential role in the era of personalised therapy for cancer patients including lung adenocarcinoma (LUAD). Long noncoding RNA (LncRNA), a relatively novel class of RNA, has shown to play a crucial role in all the areas of cancer biology. Here, we developed and validated a robust LncRNA-based prognostic signature for LUAD patients using three different cohorts.

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Lung Adenocarcinoma (LUAD) is the most common cause of lung cancer-related deaths. Long non-coding RNAs (LncRNAs) play an essential role in cancer development and progression. In this study, we identified PILAR1, a prognostic and overexpressed LncRNA, using multiple independent datasets of LUAD patients.

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Kidney Renal Clear Cell Carcinoma (KIRC) is a significant cause of cancer-related deaths. Here, we aim to identify the LncRNAs associated with the immune system and characterise their clinical utility in KIRC. A total of 504 patients' data was used from TCGA-GDC.

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Aim: LncRNAs may act as promising biomarkers in esophageal cancer (EC). Here, we illustrate the LncRNA profile and their clinical relevance in EC.

Patients & Methods: In this study, we utilized the Cancer Genome Atlas RNA-sequencing and clinical data from 186 patients and 13 normal samples.

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