Biology subjects

Riaz, N.

Publications and source records attributed to Riaz, N..

9 recordsLinked to original sources

bioRxiv2026

Neoantigen-reactive CD8+ T cell engagement marks exceptional survivors of pancreatic cancer

Pancreatic cancer (PC) is largely refractory to immune checkpoint blockade (ICB), although homologous recombination-deficient (HRD) tumors may derive benefit. In the POLAR trial of maintenance pembrolizumab plus olaparib after platinum-based chemotherapy for metastatic PC, responses remained heterogeneous. To define determinants of productive antitumor immunity, we integrated longitudinal blood TCR sequencing with tumor single-cell and spatial profiling. Durable benefit was associated with rare tumor-infiltrating, peripherally expanding (TIE) CD8+ T cell clonotypes, a subset of which were functionally neoantigen-reactive. TIE patients showed markedly prolonged survival beyond established genomic and immune biomarkers. Conversely, resistance was associated with spatial T cell exclusion, myCAF-rich stromal remodeling, basal-like/KRAS-associated malignant-cell programs, and expansion of CTLA4 regulatory T cells linked to local immunosuppressive remodeling. These findings define a clonotype-resolved framework for immune monitoring and identify complementary stromal, tumor-intrinsic, and regulatory immune barriers that may guide rational combination immunotherapy in PC.

cancer biology↗

bioRxiv2026

POLQ-driven repair scars shape the immunogenic landscape of homologous recombination-deficient pancreatic cancer

Pancreatic cancer (PC) is broadly resistant to immune checkpoint blockade, although a subset of homologous recombination-deficient (HRD) tumors exhibits durable immune engagement. The genomic features that distinguish these immune-responsive tumors from immune-inert HRD tumors remain poorly understood. Here we identify a microhomology-mediated end joining (MMEJ) repair scar, the MMEJ Deletion Footprint (MDF), as a genomic readout of POLQ-associated error-prone repair that enriches for frameshift indels. Across the multi-omic discovery cohort integrating tumor genomics, single-nucleus transcriptomics and spatial immune profiling, MDF-high HRD PC exhibited increased frameshift-indel-derived neoantigens and interferon programs. MDF was further associated with remodeling of the myeloid compartment toward MHC II-high dendritic cell-like antigen-presenting macrophage states and the immune synapse architecture marked by increased spatial interaction between APC-like macrophages and cytotoxic CD8+ T cells. These tissue-level features aligned with a functional trajectory shift of CD8+ T cells, consistent with effective anti-tumor immunity and was associated with favorable clinical outcomes of patients. Together, our findings position MMEJ-linked repair scarring as actionable biology that connects an HRD genotype to immune organization and suggests rational immunotherapy combinations that may enhance antigen presentation and myeloid activation to extend durable benefit in HRD-lineage cancers.

cancer biology↗

bioRxiv2025

RNA Transcripts Serve as a Template for Double-Strand Break Repair in Human Cells

Double-strand breaks (DSBs) are toxic lesions that lead to genome instability. While canonical DSB repair pathways typically operate independently of RNA, emerging evidence suggests that RNA:DNA hybrids and transcripts near damaged sites can influence repair outcomes. However, a direct role for transcript RNA as a template during DSB repair in human cells is yet to be established. In this study, we designed fluorescent- and sequencing-based assays, which demonstrated that RNA-containing oligonucleotides and messenger RNA serve as templates to promote DSB repair. We conducted a CRISPR/Cas9-based genetic screen to identify factors that promote RNA-templated DSB repair (RT-DSBR), and of the candidate polymerases, we identified DNA polymerase-zeta (Pol{zeta}) as the potential reverse transcriptase that facilitates RT-DSBR. Furthermore, by analyzing sequencing data from cancer genomes, we identified the presence of whole intron deletions, a unique genomic scar reflective of RT-DSBR activity generated when spliced mRNA serves as the repair template. These findings highlight RT-DSBR as an alternative pathway for repairing DSBs in transcribed genes, with potential mutagenic consequences.

molecular biology↗

bioRxiv2024

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer1-7, however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naive hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

cancer biology↗

bioRxiv2023

Multi-Scale Geometric Network Analysis Identifies Melanoma Immunotherapy Response Gene Modules

Melanoma response to immune-modulating therapy remains incompletely characterized at the molecular level. In this study, we assess melanoma immunotherapy response using a multi-scale network approach to identify gene modules with coordinated gene expression in response to treatment. Using gene expression data of melanoma before and after treatment with nivolumab, we modeled gene expression changes in a correlation network and measured a key network geometric property, dynamic Ollivier-Ricci curvature, to distinguish critical edges within the network and reveal multi-scale treatment-response gene communities. Analysis identified six distinct gene modules corresponding to sets of genes interacting in response to immunotherapy. One module alone, overlapping with the nuclear factor kappa-B pathway (NFKB), was associated with improved patient survival and a positive clinical response to immunotherapy. This analysis demonstrates the usefulness of dynamic Ollivier-Ricci curvature as a general method for identifying information-sharing gene modules in cancer.

bioinformatics↗

bioRxiv2020

Multivariate Analysis Of Potato Genotypes For Genetic Diversity

Sustainable production of food crops relies on germplasm improvement and genetic diversity that helps to identify appropriate parents, which is very important step in breeding of genotypes having high yield potential for future use. This study was conducted to investigate the extent of genetic diversity using multivariate technique on the basis of qualitative and quantitative traits. An experiment was comprised of 74 exotic genotypes and started at National Agriculture Research Center Islamabad, Pakistan during autumn 2017-2018 and 2018-2019. Data was recorded on qualitative and quantitative traits by following standard procedures and Biplot analysis was used to calculate the significance among the studied quantitative traits to exhibit the strength of relationship between traits. Results showed significant diversity in qualitative traits and quantitative traits. Red, yellowish, brown, light yellow, light brown color tubers were produced. Alike, genotypes produced yellow, cream and white flesh color tubers. Genotypes had oval, round, oblong, elliptic and reform with medium, small and large size tubers. Alike, brown, light brown, dark red and yellow eyes color was noted. In case of quantitative traits, genotypes had high variance regarding plant height, leaf area and number of tubers per lane. Genotypes had very high genetic variance for weight of tuber per plant and weight of tuber per lane while low variance was recorded for germination, number of stem per plant and number of eyes per tuber. Significant positive correlation was observed between number of tubers per plant (TPP) with number of eyes on tubers (r = 0.241) and number of tubers per lane (TPL) (r = 0.349). But negative correlation was noted between number of tubers per plant (TPP) with plant height (r = - 246), leaf area (-0.529) and germination (r = -0.283). Plant height was found significantly positive correlated with leaf area (r= 0.456), germination percentage (r = 0.255) and weight of tubers per plant (r = 0.307). Leaf area (LA) showed positive significant correlation with number of tubers per plant (r = 0.466) and weight of tubers per plant (r = 0.263)., yield and harvest index (r = 0.798, 0.755, 0.255). Weight of tubers per lane (WTL) showed positive correlation with weight of tubers per plant (r = 0.387). Regarding the interrelation between the traits and genotypes, the first two principal component axes (PC1, 24.83% and PC2, 23.46%) accounted for about 48.29% of the total variability reflecting the complexity of the variation between the plotted traits of genotypes.

genetics↗

bioRxiv2019

Novel patterns of complex structural variation revealed across thousands of cancer genome graphs

Cancer genomes often harbor hundreds of somatic DNA rearrangement junctions, many of which cannot be easily classified into simple (e.g. deletion, translocation) or complex (e.g. chromothripsis, chromoplexy) structural variant classes. Applying a novel genome graph computational paradigm to analyze the topology of junction copy number (JCN) across 2,833 tumor whole genome sequences (WGS), we introduce three complex rearrangement phenomena: pyrgo, rigma, and tyfonas. Pyrgo are "towers" of low-JCN duplications associated with early replicating regions and superenhancers, and are enriched in breast and ovarian cancers. Rigma comprise "chasms" of low-JCN deletions at late-replicating fragile sites in esophageal and other gastrointestinal (GI) adenocarcinomas. Tyfonas are "typhoons" of high-JCN junctions and fold back inversions that are enriched in acral but not cutaneous melanoma and associated with a previously uncharacterized mutational process of non-APOBEC kataegis. Clustering of tumors according to genome graph-derived features identifies subgroups associated with DNA repair defects and poor prognosis.

genomics↗

bioRxiv2019

Reproducibility test of radiomics using network analysis and Wasserstein K-means algorithm

PurposeTo construct robust and validated radiomic predictive models, the development of a reliable method that can identify reproducible radiomic features robust to varying image acquisition methods and other scanner parameters should be preceded with rigorous validation. Due to the property of high correlation present between radiomic features, we hypothesize that reproducible radiomic features across different datasets that are obtained from different image acquisition settings preserve some level of connectivity between features in the form of a network.\n\nMethodsWe propose a regularized partial correlation network to identify robust and reproducible radiomic features. This approach was tested on two radiomic feature sets generated with two different reconstruction methods from a cohort of 47 lung cancer patients. The commonality of the resulting two networks was assessed. A largest common network component from the two networks was tested on phantom data consisting of 5 cancer samples. We further propose a novel K-means algorithm coupled with the optimal mass transport (OMT) theory to cluster samples. This approach following the regularized partial correlation analysis was tested on computed tomography (CT) scans from 77 head and neck cancer patients that were downloaded from The Cancer Imaging Archive (TCIA) and validated on CT scans from 83 head and neck cancer patients treated at our institution.\n\nResultsCommon radiomic features were found in relatively large network components between the resulting two partial correlation networks from a cohort of 47 lung cancer patients. The similarity of network components in terms of the common number of radiomic features was statistically significant. For phantom data, the Wasserstein distance on a largest common network component from the lung cancer data was much smaller than the Wasserstein distance on the same network using random radiomic features, implying the reliability of those radiomic features present in the network. Further analysis using the proposed Wasserstein K-means algorithm on TCIA head and neck cancer data showed that the resulting clusters separate tumor subsites and this was validated on our institution data.\n\nConclusionsWe showed that a network-based analysis enables identifying reproducible radiomic features. This was validated using phantom data and external data via the Wasserstein distance metric and the proposed Wasserstein K-means method.

biophysics↗

bioRxiv2017

Multi-dimensional genomic analysis of myoepithelial carcinoma identifies prevalent oncogenic gene fusions

Myoepithelial carcinoma (MECA) is an aggressive type of salivary gland cancer with largely unknown molecular features. MECA may arise de novo or result from oncogenic transformation of a pre-existing pleomorphic adenoma (MECA ex-PA). We comprehensively analyzed the molecular alterations in MECA with integrated genomic analyses. We identified a low mutational load (0.5/MB), but a high prevalence of fusion oncogenes (28/40 tumors; 70%). We found FGFR1-PLAG1 in 7 (18%) cases, and the novel TGFBR3-PLAG1 fusion in 6 (15%) cases. TGFBR3-PLAG1 was specific for MECA de novo tumors or the malignant component of MECA ex-PA, was absent in 723 other salivary gland tumors, and promoted a tumorigenic phenotype in vitro. We discovered other novel PLAG1 fusions, including ND4-PLAG1, which is an oncogenic fusion between mitochondrial and nuclear DNA. One tumor harbored an MSN-ALK fusion, which was tumorigenic in vitro, and targetable with ALK inhibitors. Certain gene fusions were predicted to result in neoantigens with high MHC binding affinity. A high number of copy number alterations was associated with poorer prognosis. Our findings indicate that MECA is a fusion-driven disease, nominate TGFBR3-PLAG1 as a hallmark of MECA, and provide a framework for future steps of diagnostic and therapeutic research in this lethal cancer.

cancer biology↗