S6K1 is a Targetable Vulnerability in Tumors Exhibiting Plasticity and Therapy Resistance
Background: Most tumors initially respond to treatment, yet refractory clones subsequently develop owing to resistance mechanisms associated with cancer cell plasticity and heterogeneity. Methods: We used a chemical biology approach to identify…
by Saptadwipa Ganguly, Ravshan Burikhanov, Vitaliy M. Sviripa, Sally Ellingson, Jieyun Jiang, Christian M. Gosser, David Orren, Eva M. Goellner, Gautham G. Shenoy, Mahadev Rao, John D’Orazio, Christine F. Brainson, Chang-Guo Zhan, Peter H. Spielmann, David S. Watt, and Vivek M. Rangnekar
Int J Biol Sci 2025; 21(2):454-472
Impact Factor: 8.2
Prognostic Indicators for Precision Treatment of Non-Small Cell Lung Carcinoma
Non-small cell lung cancer (NSCLC) has established predictive biomarkers that enable decisions on treatment regimens for many patients. However, resistance to therapy is widespread. It is therefore essential to have a panel of molecular biomarkers that may help overcome therapy resistance and prevent adverse effects of treatment. We performed in silico analysis of NSCLC prognostic indicators, separately for adenocarcinomas and squamous carcinomas, by using The Cancer Genome Atlas (TCGA) and non-TCGA data sources in cBioPortal as well as UALCAN. This review describes lung cancer biology, elaborating on the key genetic alterations and specific genes responsible for resistance to conventional treatments. Importantly, we examined the mechanisms associated with resistance to immune checkpoint inhibitors. Our analysis indicated that a robust prognostic biomarker was lacking for NSCLC, especially for squamous cell carcinomas. In this work, our screening uncovered previously unidentified prognostic gene expression indicators, namely, MYO1E, FAM83 homologs, and DKK1 for adenocarcinoma, and FGA and TRIB1 for squamous cell carcinoma. It was further observed that overexpression of these genes was associated with poor prognosis. Additionally, FAM83 homolog and TRIB1 unexpectedly harbored copy number amplifications. In conclusion, this study elucidated novel prognostic indicators for NSCLC that may serve as targets to overcome therapy resistance toward improved patient outcomes.
by Damayanti Das Ghosh ,Hannah McDonald, Rajeswari Dutta, Keerthana Krishnan, Jaya Thilakan, Manash K. Paul, Neha Arya, Mahadev Rao, and Vivek M. Rangnekar
Cells 2024, 3(21), 1785
Impact Factor: 5.1
Molecular Susceptibility and Treatment Challenges in Melanoma
Melanoma is the most aggressive subtype of cancer, with a higher propensity to spread compared to most solid tumors. The application of OMICS approaches has revolutionized the field of melanoma research by providing comprehensive insights into the molecular alterations and biological processes underlying melanoma development and progression. This review aims to offer an overview of melanoma biology, covering its transition from primary to malignant melanoma, as well as the key genes and pathways involved in the initiation and progression of this disease. Utilizing online databases, we extensively explored the general expression profile of genes, identified the most frequently altered genes and gene mutations, and examined genetic alterations responsible for drug resistance. Additionally, we studied the mechanisms responsible for immune checkpoint inhibitor resistance in melanoma.
by Kiran Kumar Kolathur, Radhakanta Nag, Prathvi V Shenoy, Yagya Malik, Sai Manasa Varanasi, Ramcharan Singh Angom, Debabrata Mukhopadhyay
Cells 2024, 13(16), 1383
Impact Factor: 5.1
KRAS Mutation Subtypes and Their Association with Other Driver Mutations in Oncogenic Pathways
The KRAS mutation stands out as one of the most influential oncogenic mutations, which directly regulates the hallmark features of cancer and interacts with other cancer-causing driver mutations. However, there remains a lack of precise information on their cooccurrence with mutated variants of KRAS and any correlations between KRAS and other driver mutations. To enquire about this issue, we delved into cBioPortal, TCGA, UALCAN, and Uniport studies. We aimed to unravel the complexity of KRAS and its relationships with other driver mutations. We noticed that G12D and G12V are the prevalent mutated variants of KRAS and coexist with the TP53 mutation in PAAD and CRAD, while G12C and G12V coexist with LUAD. We also noticed similar observations in the case of PIK3CA and APC mutations in CRAD. At the transcript level, a positive correlation exists between KRAS and PIK3CA and between APC and KRAS in CRAD. The existence of the co-mutation of KRAS and other driver mutations could influence the signaling pathway in the neoplastic transformation. Moreover, it has immense prognostic and predictive implications, which could help in better therapeutic management to treat cancer.
by Koushik Mondal, Mahesh Kumar Posa, Revathi P. Shenoy and Susanta Roychoudhury
Cells 2024, 13(14), 1221
Impact Factor: 5.1
Integration of pan-omics technologies and three-dimensional in vitro tumor models: an approach toward drug discovery and precision medicine – Molecular Cancer
Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer. Graphical Abstract
by Anmi Jose, Pallavi Kulkarni, Jaya Thilakan, Murali Munisamy, Anvita Gupta Malhotra, Jitendra Singh, Ashok Kumar, Vivek M Rangnekar, Neha Arya, Mahadev Rao
Mol Cancer 2024 Mar 9;23(1):50
Impact Factor: 37.4
Predictive performance of population pharmacokinetic models of imatinib in chronic myeloid leukemia patients – Cancer Chemotherapy and Pharmacology
Background and aim Chronic myeloid leukemia is a myeloproliferative neoplasm associated with the specific chromosomal translocation known as the Philadelphia chromosome. Imatinib is a potent BCR-ABL tyrosine kinase inhibitor, which is approved as the first line therapy for CML patients. There are various population pharmacokinetic studies available in the literature for this population. However, their use in other populations outside of their cohort for the model development has not been evaluated. This study was aimed to perform the predictive performance of the published population pharmacokinetic models for imatinib in CML population and propose a dosing nomogram. Methods A systematic review was conducted through PubMed, and WoS databases to identify PopPK models. Clinical data collected in adult CML patients treated with imatinib was used for evaluation of these models. Various prediction-based metrics were used for assessing the bias and precision of PopPK models using individual predictions. Results Eight imatinib PopPK model were selected for evaluating the model performance. A total of 145 plasma imatinib samples were collected from 43 adult patients diagnosed with CML and treated with imatinib. The PopPK model reported by Menon et al. had better performance than all other PopPK models. Conclusion Menon et al. model was able to predict well for our clinical data where it had the relative mean prediction error percentage ≤ 20%, relative median absolute prediction error ≤ 30% and relative root mean square error close to zero. Based on this final model, we proposed a dosing nomogram for various weight groups, which could potentially help to maintain the trough concentrations in the therapeutic range.
by Jaya Shree Dilli Batcha, Vikram Gota, Saikumar Matcha, Arun Prasath Raju, Mahadev Rao, Karthik S. Udupa, Surulivelrajan Mallayasamy
Cancer Chemother Pharmacol 2024 Mar 5
Impact Factor: 2.7
Increased Gene Expression of C1orf74 Is Associated with Poor Prognosis in Cervical Cancer
C1orf74, also known as URCL4, has been reported to have higher expression and be associated with poor prognosis in lung adenocarcinoma patients, and its role in regulation of the EGFR/AKT/mTORC1 pathway has been recently elucidated. In the current study, we used publicly available data and experimen…
by Preetiparna Parida, Shirley Lewis, Krishna Sharan, Mehta Vedant Kamal, Naveena A. N. Kumar, Vishwapriya M. Godkhindi, Sooryanarayana Varambally, Vivek M. Rangnekar, Mahadev Rao, and Rama Rao Damerla
Cells 2023, 12(21), 2530.
Impact Factor: 6.0
Insights from a Computational-Based Approach for Analyzing Autophagy Genes across Human Cancers
In the last decade, there has been a boost in autophagy reports due to its role in cancer progression and its association with tumor resistance to treatment. Despite this, many questions remain to be elucidated and explored among the different tumors. Here, we used omics-based cancer datasets to identify autophagy genes as prognostic markers in cancer. We then combined these findings with independent studies to further characterize the clinical significance of these genes in cancer. Our observations highlight the importance of innovative approaches to analyze tumor heterogeneity, potentially affecting the expression of autophagy-related genes with either pro-tumoral or anti-tumoral functions. In silico analysis allowed for identifying three genes (TBC1D12, KERA, and TUBA3D) not previously described as associated with autophagy pathways in cancer. While autophagy-related genes were rarely mutated across human cancers, the expression profiles of these genes allowed the clustering of different cancers into three independent groups. We have also analyzed datasets highlighting the effects of drugs or regulatory RNAs on autophagy. Altogether, these data provide a comprehensive list of targets to further the understanding of autophagy mechanisms in cancer and investigate possible therapeutic targets.
by Alexis Germán Murillo Carrasco, Guilherme Giovanini, Alexandre Ferreira Ramos, Roger Chammas and Silvina Odete Bustos
Genes 2023, 14(8), 1550
Impact Factor: 2.8
Crizotinib induces Par-4 secretion from normal cells and GRP78 expression on the cancer cell surface for selective tumor growth inhibition
Lung cancer is the leading cause of cancer-related deaths. Lung cancer cells develop resistance to apoptosis by suppressing the secretion of the tumor suppressor Par-4 protein (also known as PAWR) and/or down-modulating the Par-4 receptor GRP78 on the…
by Ravshan Burikhanov, Saptadwipa Ganguly, Sally Ellingson, Vitaliy M Sviripa, Nathalia Araujo, Shunqiang Li, Prasanna Venkatraman, Mahadev Rao, Anuradha Choughule, Christine F Brainson, Chang-Guo Zhan, H Peter Spielmann, David S Watt, Ramaswamy Govindan, Vivek M Rangnekar
American Journal of Cancer Research 2023;13(3):976-991.
Impact Factor: 5.942
Factors Influencing Pharmacokinetics of Tamoxifen in Breast Cancer Patients: A Systematic Review of Population Pharmacokinetic Models
Background: Tamoxifen is useful in managing breast cancer and it is reported to have significant variability in its pharmacokinetics. This review aimed to summarize reported population pharmacokinetics studies of tamoxifen and to identify the factors affecting the pharmacokinetics of tamoxifen in ad…
by Jaya Shree Dilli Batcha, Arun Prasath Raju, Saikumar Matcha, Elstin Anbu Raj S., Karthik S. Udupa, Vikram Gota and Surulivelrajan Mallayasamy
Biology 2023, 12(1), 51
Impact Factor: 5.168
Local data commons: the sleeping beauty in the community of data commons – BMC Bioinformatics
Background Public Data Commons (PDC) have been highlighted in the scientific literature for their capacity to collect and harmonize big data. On the other hand, local data commons (LDC), located within an institution or organization, have been underrepresented in the scientific literature, even thou…
by Jong Cheol Jeong, Isaac Hands, Jill M. Kolesar, Mahadev Rao, Bront Davis, York Dobyns, Joseph Hurt-Mueller, Justin Levens, Jenny Gregory, John Williams, Lisa Witt, Eun Mi Kim, Carlee Burton, Amir A. Elbiheary, Mingguang Chang & Eric B. Durbin
BMC Bioinformatics volume 23, Article number: 386 (2022)
Impact Factor: 3.169
Integration of liquid biopsy and pharmacogenomics for precision therapy of EGFR mutant and resistant lung cancers – PubMed
The advent of molecular profiling has revolutionized the treatment of lung cancer by comprehensively delineating the genomic landscape of the epidermal growth factor receptor (EGFR) gene. Drug resistance caused by EGFR mutations and genetic polymorphisms of drug metabolizing enzymes and transporters…
by Kolesar J, Peh S, Thomas L, Baburaj G, Mukherjee N, Kantamneni R, Lewis S, Pai A, Udupa KS, Kumar An N, Rangnekar VM, Rao M.
Mol Cancer. 2022 Feb 24;21(1):61.
Impact Factor: 41.14
Raman micro-spectroscopic map estimating in vivo precision of tumor ablative effect achieved by photothermal therapy procedure – PubMed
Photothermal-therapy (PTT) inculcates near-infrared laser guided local heating effect, where high degree of precision is expected, but not well proven to-date. An ex vivo tissue biochemical map with molecular/biochemical response showing the coverage area out of an optimized PTT procedure can reveal…
by Sumit K.Mishra, Arti Hole, B. Pradeep K.Reddy, Rohit Srivastava, Murali Krishna Chilakapati, Abhijit De
Nanomedicine 2021 Oct;37:102437.
Impact Factor: 6.5
Therapeutic opportunities in cancer therapy: targeting the p53-MDM2/MDMX interactions – PubMed
Ubiquitination is a key enzymatic post-translational modification that influences p53 stability and function. p53 protein regulates the expression of MDM2 (mouse double-minute 2 protein) E3 ligase and MDMX (double-minute 4 protein), through proteasome-based degradation. Exploration of targeting the…
by Munisamy M, Mukherjee N, Thomas L, Pham AT, Shakeri A, Zhao Y, Kolesar J, Rao PPN, Rangnekar VM, Rao M.
Am J Cancer Res. 2021 Dec 15;11(12).
Impact Factor: 6.166
Value added by an inter-continental cancer consortium – PubMed
Value added by an inter-continental cancer consortium
by Rao M, Venkatraman P, Mukhopadhyay D, Roychoudhury S, Vanderford NL, Rangnekar VM.
Genes Cancer. 2021 May 21;12:65-68.
Impact Factor: 5.666
DACH1 mutation frequency in endometrial cancer is associated with high tumor mutation burden – PubMed
DACH1 mutations are prevalent in Kentucky patients with endometrial cancer. These mutations are associated with high tumor mutational burden and co-occur with genome destabilizing gene mutations. These findings suggest DACH1 may be a candidate biomarker for future trials with immunotherapy, particul…
by Riggs MJ, Lin N, Wang C, Piecoro DW, Miller RW, Hampton OA, Rao M, Ueland FR, Kolesar JM.
PLoS One. 2020 Dec 30;15(12).
Impact Factor: 3.240
Liquid biopsy approaches for pleural effusion in lung cancer patients – PubMed
Genomic profiling of tumors has become the mainstay for diagnosis, treatment monitoring and a guide to precision medicine. However, in clinical practice, the detection of driver mutations in tumors has several procedural limitations owing to progressive disease and tumor heterogeneity. The current e…
by Baburaj G, Damerla RR, Udupa KS, Parida P, Munisamy M, Kolesar J, Rao M.
Mol Biol Rep. 2020 Oct;47(10)
Impact Factor: 2.316
Histone Demethylase KDM5B as a Therapeutic Target for Cancer Therapy – PubMed
Lysine-specific demethylase 5B (KDM5B/PLU1/JARID1B) is found to be overexpressed in numerous malignancies, including breast, lung, skin, liver, and prostate cancer. Identification of molecules targeting the KDM5B enzyme could be a potential lead in cancer research. Although many KDM5B inhibitors wit…
by Jose A, Shenoy GG, Sunil Rodrigues G, Kumar NAN, Munisamy M, Thomas L, Kolesar J, Rai G, Rao PPN, Rao M.
Cancers (Basel). 2020 Jul 31;12(8):2121.
Impact Factor: 6.639
Potential Utility of Liquid Biopsy as a Diagnostic and Prognostic Tool for the Assessment of Solid Tumors: Implications in the Precision Oncology – PubMed
Liquid biopsy is a technique that utilizes circulating biomarkers in the body fluids of cancer patients to provide information regarding the genetic landscape of the cancer. It is emerging as an alternative and complementary diagnostic and prognostic tool to surgical biopsy in oncology. Liquid biops…
by Mathai RA, Vidya RVS, Reddy BS, Thomas L, Udupa K, Kolesar J, Rao M.
J Clin Med. 2019 Mar 18;8(3):373.
Impact Factor: 4.242
