Biology subjects

Najumudeen, A. K.

Publications and source records attributed to Najumudeen, A. K..

7 recordsLinked to original sources

bioRxiv2023

KRAS allelic imbalance drives tumour initiation yet suppresses metastasis in colorectal cancer in vivo

Oncogenic KRAS mutations are well-described functionally and are known to drive tumorigenesis. Recent reports describe a significant prevalence of KRAS allelic imbalances or gene dosage changes in human cancers, including loss of the wild-type allele in KRAS mutant cancers. However, there is still much debate over the function of wild-type KRAS in tumour initiation, progression and therapeutic response. We have developed a genetically engineered mouse model which allows deletion of the wild-type copy of Kras in the context of an intact oncogenic Kras in colorectal cancer. We observe that in the presence of oncogenic Kras, wild-type Kras acts to restrain tumour growth. Mechanistically, deletion of wild-type Kras exacerbates oncogenic KRAS signalling through MAPK and thus drives tumour initiation. Absence of wild-type Kras potentiates the oncogenic effect of KRASG12D, while presence of wild-type Kras is associated with resistance to inhibition of MEK1/2 in KRASG12D driven tumours. Importantly, loss of wild-type Kras in oncogenic KRAS-driven aggressive tumours significantly alters tumour progression, metastasis while impacting tumour immune cell infiltration. This study demonstrates a suppressive role for wild-type Kras during colon tumour initiation and highlights the critical impact of wild-type Kras upon therapeutic response to MAPK and tumour progression in Kras mutant cancers. HighlightsO_LIWild-type KRAS suppresses mutant KRASG12D mediated proliferation and signalling in colorectal cancer models in vivo C_LIO_LIConcomitant loss of wild-type KRAS and activation of WNT signalling promotes mutant KRAS-driven tumour initiation. C_LIO_LIWild-type KRAS promotes resistance to MAPK inhibition in KRAS mutant tumours C_LIO_LILoss of wild-type KRAS inhibits metastasis of late-stage mutant KRAS colorectal cancer models. C_LI

cancer biology↗

bioRxiv2023

Kras loss of heterozygosity promotes MAPK dependent pancreatic ductal adenocarcinoma and induces therapeutic sensitivity

Pancreatic cancer is characterised by the prevalence of oncogenic mutations in KRAS. Previous studies have reported that altered Kras gene dosage drives progression and metastatic incidence in pancreatic cancer. While the role of oncogenic KRAS mutation is well characterised, the relevance of the partnering wild-type KRAS allele in pancreatic cancer is less well understood and controversial. Using in vivo mouse modelling of pancreatic cancer, we demonstrate that wild-type Kras restrains the oncogenic impact of mutant Kras, and drastically impacts both Kras-mediated tumourigenesis and therapeutic response. Mechanistically, deletion of wild-type Kras increases oncogenic Kras signalling through the downstream MAPK effector pathway, driving pancreatic intraepithelial neoplasia (PanIN) initiation. In addition, in the KPC mouse model, a more aggressive model of pancreatic cancer, loss of wild-type KRAS leads to accelerated initiation but delayed tumour progression. These tumours had altered stroma, downregulated Myc levels and an enrichment for immunogenic gene signatures. Importantly, loss of wild-type Kras sensitises Kras mutant tumours to MEK1/2 inhibition though tumours eventually become resistant and then rapidly progress. This study demonstrates the repressive role of wild-type Kras during pancreatic tumourigenesis and highlights the critical impact of the presence of wild-type KRAS on tumourigenesis and therapeutic response in pancreatic cancer.

cancer biology↗

bioRxiv2023

Metabolic profiling stratifies colorectal cancer and reveals adenosylhomocysteinase as a therapeutic target

With colorectal cancer (CRC) being the second most common cause of cancer-related deaths worldwide1, there is an urgent need for better diagnostic tools and new, more targeted therapies. Here we used genetically engineered mouse models (GEMMs), and multimodal mass spectrometry-based metabolomics to study the impact of common genetic drivers of CRC on the metabolic landscape of the intestine. We show that unsupervised metabolic profiling can stratify intestinal tissues according to underlying genetic alterations, and use mass spectrometry imaging (MSI) to identify tumour, stromal and normal adjacent tissues. By identifying ions that drive variation between normal and transformed tissues, we found dysregulation of the methionine cycle to be a hallmark of APC-mutant CRC, and propose one of its enzymes, i.e. adenosylhomocysteinase (AHCY), as a new therapeutic target. Collectively, we show that the profound genotype-dependent alterations in both lipid and small molecule metabolism in CRC may be exploited for tissue classification with no need for ion identification, and we applied further data analysis to expose a novel metabolic vulnerability of CRC.

cancer biology↗

bioRxiv2022

Targeting a broad spectrum of KRAS-mutant cancers by hyperactivation-induced cell death

The KRAS oncogene drives many common and highly fatal malignancies. These include pancreatic, lung, and colorectal cancer, where numerous different activating KRAS mutations have made the development of KRAS inhibitors difficult. Here we identify the scaffold protein SH3 and multiple ankyrin repeat domain 3 (SHANK3) as a RAS interactor that binds overactive mutant forms to limit oncogenic KRAS signalling and maintain RAS- activity at an optimal level. Depletion of SHANK3 results in hyperactivation of KRAS/mitogen-activated protein kinase (MAPK) signalling, which in turn selectively induces MAPK/ERK-dependent cell death in KRAS-mutant cancers. Furthermore, targeting of this therapeutic vulnerability through nanobody- or RNA interference- mediated disruption of the SHANK3-KRAS interaction reduces tumour growth in vivo. Thus, inhibition of the SHANK3-KRAS interaction represents a new pan-KRAS-mutant compatible strategy for selective killing of KRAS- mutant cancer cells through excessive signalling. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/508660v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@87e71forg.highwire.dtl.DTLVardef@56cf94org.highwire.dtl.DTLVardef@1561136org.highwire.dtl.DTLVardef@183f711_HPS_FORMAT_FIGEXP M_FIG C_FIG Schematic model of SHANK3-controlled cell fate in KRAS-mutant cancers. SHANK3 directly interacts with KRAS and competes with RAF for KRAS binding to sustain oncogenic RAS-MAPK/ERK signalling at an optimal level (i.e. below toxic oncogenic signalling) in KRAS-mutant cancers. SHANK3 silencing (1) and inhibition of SHANK3-KRAS interaction (2) drive KRAS-mutant cells into cell death.

cancer biology↗

bioRxiv2022

Aspirin reprogrammes colorectal cancer cell metabolism and sensitises to glutaminase inhibition

To support proliferation and survival within a challenging microenvironment, cancer cells must reprogramme their metabolism. As such, targeting cancer cell metabolism is a promising therapeutic avenue. However, identifying tractable nodes of metabolic vulnerability in cancer cells is challenging due to their metabolic plasticity. Identification of effective treatment combinations to counter this is an active area of research. Aspirin has a well-established role in cancer prevention, particularly in colorectal cancer (CRC), although the mechanisms are not fully understood. Here, we comprehensively characterise the metabolic impact of long-term aspirin exposure (2-4mM for 52 weeks) on CRC cells. We show that aspirin regulates several enzymes and transporters of central carbon metabolism and results in a reduction in glutaminolysis and a concomitant increase in glucose metabolism, demonstrating reprogramming of nutrient utilisation. We show that aspirin causes likely compensatory changes that renders the cells sensitive to the glutaminase 1 (GLS1) inhibitor - CB-839. Of note given the clinical interest, treatment with CB-839 alone had little effect on CRC cell growth or survival. However, in combination with aspirin, CB-839 inhibited CRC cell proliferation and induced apoptosis in vitro, and importantly, reduced crypt proliferation in Apcfl/fl mice in vivo. Together, these results show that aspirin leads to significant metabolic reprogramming in colorectal cancer cells and raises the possibility that aspirin could significantly increase the efficacy of metabolic cancer therapies in CRC.

cancer biology↗

bioRxiv2022

Molecular phenotyping of colorectal neoplasia shows dynamic and adaptive cancer stem cell population admixture

Intestinal homeostasis is underpinned by LGR5+ve crypt-base columnar stem cells (CBCs), but following injury, dedifferentiation results in the emergence of LGR5-ve regenerative stem cell populations (RSCs), characterised by fetal transcriptional profiles. Neoplasia hijacks regenerative signalling, so we assessed the distribution of CBCs and RSCs in mouse and human intestinal tumors. Using combined molecular-morphological analysis we demonstrate variable expression of stem cell markers across a range of lesions. The degree of CBC-RSC admixture was associated with both epithelial mutation and microenvironmental signalling disruption, and could be mapped across disease molecular subtypes. The CBC-RSC equilibrium was adaptive, with a dynamic response to acute selective pressure, and adaptability was associated with chemoresistance. We propose a fitness landscape model where individual tumors have equilibrated stem cell population distributions along a CBC-RSC phenotypic axis. Cellular plasticity is represented by position shift along this axis, and is influenced by cell-intrinsic, extrinsic and therapeutic selective pressures.

cancer biology↗

bioRxiv2020

Training a neural network to learn other dimensionality reduction removes data size restrictions in bioinformatics and provides a new route to exploring data representations

High dimensionality omics and hyperspectral imaging datasets present difficult challenges for feature extraction and data mining due to huge numbers of features that cannot be simultaneously examined. The sample numbers and variables of these methods are constantly growing as new technologies are developed, and computational analysis needs to evolve to keep up with growing demand. Current state of the art algorithms can handle some routine datasets but struggle when datasets grow above a certain size. We present a training deep learning via neural networks on non-linear dimensionality reduction, in particular t-distributed stochastic neighbour embedding (t-SNE), to overcome prior limitations of these methods. One Sentence SummaryAnalysis of prohibitively large datasets by combining deep learning via neural networks with non-linear dimensionality reduction.

bioinformatics↗