Biology subjects

Kravchenko-Balasha, N.

Publications and source records attributed to Kravchenko-Balasha, N..

4 recordsLinked to original sources

bioRxiv2025

Tear fluid as noninvasive liquid biopsy reveals proteins associated with malignant transformation of oral lesions

Oral leukoplakias (OLs) are premalignant lesions that can progress into oral squamous cell carcinoma (OSCC). This study hypothesized that tear fluid, as a noninvasive biofluid, reflects proteomic alterations associated with malignant transformation. The tear proteome of 44 individuals, including healthy controls, OL/PVL (proliferative verrucous leukoplakia), and OSCC patients, was deeply profiled, revealing 828 protein groups clustered according to histopathological alterations. N-glycoproteome analysis identified immune-related proteins, while public RNA-seq integration indicated immune imbalance marked by increased B-cell and decreased macrophage signatures during disease progression. Several immune-associated proteins and epithelial markers, including desmoplakin, KRT14, and DSC1, emerged as potential indicators of malignant transformation. These findings demonstrate that tear fluid reflects oral carcinogenic processes, thereby serving as a noninvasive liquid biopsy for early detection and clinical monitoring.

biochemistry↗

bioRxiv2021

Mapping cellular subpopulations within triple negative breast cancer tumors provides a tool for cancer sensitization to radiotherapy

Triple negative breast cancer (TNBC) is an aggressive type of cancer that is known to be resistant to radiotherapy (RT). Evidence is accumulating that is indicative of the plasticity of TNBC, where one cancer subtype switches to another in response to various treatments, including RT. In this study we aim to overcome tumor resistance by designing TNBC-sensitizing targeted therapies that exploit the plasticity occurring due to radiation exposure. Using single cell analysis of molecular changes occurring in irradiated TNBC tumors, we identified two initially undetected distinct subpopulations, represented by overexpressed Her2 and cMet, expanding post-RT and persisting in surviving tumors. Using murine cancer models and patient-derived TNBC tumors, we showed that only simultaneous targeting of Her2 and cMet was successful in sensitizing TNBC to RT and preventing its regrowth. The strategy presented herein holds the potential to be broadly applicable in clinical use. HighlightsO_LISensitization of TNBC to radiotherapy (RT) is a clinically unmet need C_LIO_LISingle cell strategy creates a precise map of subpopulations expanding post-RT C_LIO_LIEvolution of intra-tumor heterogeneity is turned into a therapeutic advantage C_LIO_LISimultaneous targeting of expanding subpopulations sensitizes TNBC to radiotherapy C_LI

cancer biology↗

bioRxiv2020

Overcoming Resistance to BRAFV600E Inhibition in Melanoma by Deciphering and Targeting Personalized Protein Network Alterations

BRAFV600E melanoma patients, despite initially responding to the clinically prescribed anti-BRAFV600E therapy, often relapse and their tumors develop drug resistance. While it is widely accepted that these tumors are originally driven by the BRAFV600E mutation, they often eventually diverge and become supported by various signaling networks. Therefore, patient-specific altered signaling signatures should be deciphered and treated individually. In this study, we design individualized melanoma combination treatments based on personalized network alterations. Using an information-theoretic approach, we compute high-resolution patient-specific altered signaling signatures. These altered signaling signatures each consist of several co-expressed subnetworks, which should all be targeted to optimally inhibit the entire altered signaling flux. Based on these data, we design smart, personalized drug combinations, often consisting of FDA-approved drugs. We validate our approach in vitro and in vivo showing that individualized drug combinations that are rationally based on patient-specific altered signaling signatures are more efficient than the clinically used anti-BRAFV600E or BRAFV600E/MEK targeted therapy. Furthermore, these drug combinations are highly selective, as a drug combination efficient for one BRAFV600E tumor is significantly less efficient for another, and vice versa. The approach presented herein can be broadly applicable to aid clinicians to rationally design patient-specific anti-melanoma drug combinations.

systems biology↗

bioRxiv2019

Meiosis and Kinetochore genes are used by cancer cells as genome destabilizers and transformation catalysts

Cancer cells have an altered transcriptome which contributes to their altered behaviors compared to normal cells. Indeed, many tumors express high levels of genes participating in meiosis or kinetochore biology, but the role of this high expression has not been fully elucidated. In this study we explore the relationship between this overexpression and genome instability and transformation capabilities of cancer cells. For this, we obtained expression data from 5 different cancer types which were analyzed using computational information-theoretic analysis. We were able to show that highly expressed meiotic/kinetochore genes were enriched in the altered gene expression subnetworks characterizing unstable cancer types with high chromosome instability (CIN). However, altered subnetworks found in the cancers with low CIN did not include meiotic and kinetochore genes. Representative gene candidates, found by the analysis to be correlated with a CIN phenotype, were further explored by transfecting genomically-stable (HCT116) and unstable (MCF7) cancer cell lines with vectors overexpressing those genes. This overexpression resulted in an increase in the numbers of abnormal cell divisions and defective spindle formations and in increased transformation properties in stable cancer HCT116 cells. Interestingly, the same properties were less affected by the overexpressed genes in the unstable MCF7 cancer cells. Our results indicate that overexpression of both meiosis and kinetochore genes is capable of driving genomic instability and cancer progression.

cancer biology↗