Biology subjects

Lim, T. K. H.

Publications and source records attributed to Lim, T. K. H..

4 recordsLinked to original sources

bioRxiv2023

Dearth of smoking-induced mutations in oncogene-driven non-small-cell lung cancer despite smoking exposure

Non-small cell lung cancers (NSCLCs) in non-smokers are mostly driven by mutations in the oncogenes EGFR, ERBB2, and MET, and fusions involving ALK and RET. We term these "non-smoking-related oncogenes" (NSROs). In addition to occurring in non-smokers, NSRO-driven tumors also occur in smokers, and the clonal architecture and genomic landscape of these tumors remain unknown. We investigated genomic and transcriptomic alterations in 173 tumor sectors from 48 patients with NSRO-driven or typical-smoking NSCLCs. NSRO-driven NSCLCs in smokers and non-smokers have similar genomic landscapes. Surprisingly, even in patients with prominent smoking histories, the mutational signature caused by tobacco smoking was essentially absent in NSRO-driven NSCLCs. However, NSRO-driven NSCLCs in smokers had higher transcriptomic activities related to regulation of the cell cycle, suggesting that smoking still affects tumor phenotype independently of genomic alterations. Statement of significanceThis study highlights the lack of genomic scars caused by smoking in NSCLCs driven by non-smoking-related oncogenes regardless of smoking history. The impact of smoking on these tumors is mainly non-genomic. The transcriptomic features of NSCLCs associated with smoking may help in the development of therapeutic approaches.

cancer biology↗

bioRxiv2021

Obtaining Spatially Resolved Tumor Purity Maps Using Deep Multiple Instance Learning In A Pan-cancer Study

Tumor purity is the proportion of cancer cells in the tumor tissue. An accurate tumor purity estimation is crucial for accurate pathologic evaluation and for sample selection to minimize normal cell contamination in high throughput genomic analysis. We developed a novel deep multiple instance learning model predicting tumor purity from H&E stained digital histopathology slides. Our model successfully predicted tumor purity from slides of fresh-frozen sections in eight different TCGA cohorts and formalin-fixed paraffin-embedded sections in a local Singapore cohort. The predictions were highly consistent with genomic tumor purity values, which were inferred from genomic data and accepted as the golden standard. Besides, we obtained spatially resolved tumor purity maps and showed that tumor purity varies spatially within a sample. Our analyses on tumor purity maps also suggested that pathologists might have chosen high tumor content regions inside the slides during tumor purity estimation in the TCGA cohorts, which resulted in higher values than genomic tumor purity values. In short, our model can be utilized for high throughput sample selection for genomic analysis, which will help reduce pathologists workload and decrease inter-observer variability. Moreover, spatial tumor purity maps can help better understand the tumor microenvironment as a key determinant in tumor formation and therapeutic response.

cancer biology↗

bioRxiv2020

scRNA-seq reveals ACE2 and TMPRSS2 expression in TROP2+ Liver Progenitor Cells: Implications in COVID-19 associated Liver Dysfunction

The recent pandemic of coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 was first reported in China (December 2019) and now prevalent in [~]170 countries across the globe. Entry of SARS-CoV-2 into mammalian cells require the binding of viral Spike (S) proteins to the ACE2 (angiotensin converting enzyme 2) receptor. Once entered the S protein is primed by a specialised serine protease, TMPRSS2 (Transmembrane Serine Protease 2) in the host cell. Importantly, beside respiratory symptoms, consistent with other common respiratory virus infection when patients become viraemic, a significant number of COVID-19 patients also develop liver comorbidities. We explored if specific target cell-type in the mammalian liver, could be implicated in disease pathophysiology other than the general deleterious response to cytokine storms. Here we employed single-cell RNA-seq (scRNA-seq) to survey the human liver and identified potentially implicated liver cell-type for viral ingress. We report the co-expression of ACE2 and TMPRSS2 in a TROP2+ liver progenitor population. Importantly, we fail to detect the expression of ACE2 in hepatocyte or any other liver (immune and stromal) cell types. These results indicated that in COVID-19 associated liver dysfunction and cell death, viral infection of TROP2+ progenitors in liver may significantly impaired liver regeneration and could lead to pathology. Highlights- EPCAM+ Liver progenitors co-express ACE2 and TMPRSS2 - ACE2 and TMPRSS2 expression is highest in TROP2high progenitors - ACE2 and TMPRSS2 cells express cholangiocyte biased fate markers - ACE2 and TMPRSS2 positive cells are absent in human fetal liver

genomics↗

bioRxiv2019

CD38 is a good predictor of anti-PD-1 immunotherapy responsiveness in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-associated mortality in the world. However, with the associated low five-year survival and high recurrence rates, alternative treatment modalities specifically immunotherapy have been researched. A correlation between CD38+ tumour-infiltrating leukocyte (TIL) density and improved prognosis was found in a recent study. However, studies relating to CD38 expression in immune infiltrates within tumours are limited. In the present study, we confirmed the expression of CD38 on macrophages in HCC and determined the relationship between CD38+ leukocytes and lymphocytes and patient response to immunotherapy. Using immunohistochemistry, we analysed tissue samples obtained from 20 patients from Singapore with HCC prior to immunotherapy. Tumour infiltrating leukocytes expression within tumour were correlated to the responsiveness of patients to immunotherapy.\n\nExpression of CD38 was found within the tumour cells and surrounding immune infiltrates including lymphocytes and macrophages. We then ask whether CD38 expression by the distinct cell populations may acquire theranostic relevance. Patients with higher level of CD38+ immune infiltrate subsets had significantly better response to anti-PD-1 immunotherapy, and this is also true for CD38+ lymphocytes within the tumour microenvironment. In particular, a cut-off of 13.0% positive out of total leukocytes and 12.4% positive out of total lymphocytes is found to be of strong predictive value of responsiveness to immunotherapy treatment, thus a strong theranostic impact is seen by using CD38 as a biomarker for anti-PD-1 therapy.\n\nThe establishment of an association between CD38 expression and the response to anti-PD-1 immunotherapy in HCC, could be applied to a larger cohort outside Singapore. These may eventually change the routine testing in clinical practice to identify HCC patients suitable for immunotherapy.

cancer biology↗