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Cancers often overexpress multiple clinically relevant oncogenes, but it is not known if combinations of oncogenes in cellular subpopulations within a cancer influence clinical outcomes. Using quantitative multispectral imaging of the prognostically relevant oncogenes MYC, BCL2, and BCL6 in diffuse large B-cell lymphoma (DLBCL), we show that the percentage of cells with a unique combination MYC+BCL2+BCL6− (M+2+6−) consistently predicts survival across four independent cohorts (n = 449), an effect not observed with other combinations including M+2+6+. We show that the M+2+6− percentage can be mathematically derived from quantitative measurements of the individual oncogenes and correlates with survival in IHC (n = 316) and gene expression (n = 2,521) datasets. Comparative bulk/single-cell transcriptomic analyses of DLBCL samples and MYC/BCL2/BCL6-transformed primary B cells identify molecular features, including cyclin D2 and PI3K/AKT as candidate regulators of M+2+6− unfavorable biology. Similar analyses evaluating oncogenic combinations at single-cell resolution in other cancers may facilitate an understanding of cancer evolution and therapy resistance. Significance: Using single-cell–resolved multiplexed imaging, we show that selected subpopulations of cells expressing specific combinations of oncogenes influence clinical outcomes in lymphoma. We describe a probabilistic metric for the estimation of cellular oncogenic coexpression from IHC or bulk transcriptomes, with possible implications for prognostication and therapeutic target discovery in cancer. This article is highlighted in the In This Issue feature, p. 1027

Excessive genomic instability coupled with abnormalities in DNA repair pathways induces high levels of 'replication stress' when cancer cells propagate. Rather than hampering cancer cell proliferation, novel treatment strategies are turning their attention towards targeting cell cycle checkpoint kinases (such as ATR, CHK1, WEE1, and others) along the DNA damage response and replicative stress response pathways, thereby allowing unrepaired DNA damage to be carried forward towards mitotic catastrophe and apoptosis. The selective ATR kinase inhibitor elimusertib (BAY 1895344) has demonstrated preclinical and clinical monotherapy activity; however, reliable predictive biomarkers of treatment benefit are still lacking. In this study, using gene expression profiling of 24 cell lines from different cancer types and in a panel of ovarian cancer cell lines, we found that nuclear-specific enrichment of checkpoint kinase 1 (CHK1) correlated with increased sensitivity to elimusertib. Using an advanced multispectral imaging system in subsequent cell line-derived xenograft specimens, we showed a trend between nuclear phosphorylated CHK1 (pCHK1) staining and increased sensitivity to the ATR inhibitor elimusertib, indicating the potential value of pCHK1 expression as a predictive biomarker of ATR inhibitor sensitivity. © 2022 The Authors. The Journal of Pathology published by John WileySons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

DLBCL is the most common lymphoma with high tumor heterogeneity. Treatment refractoriness and relapse from R-CHOP therapy in patients remain a clinical problem. Activation of the non-canonical NF-κB pathway is associated with R-CHOP resistance. However, downstream targets of non-canonical NF-κB mediating R-CHOP-induced resistance remains uncharacterized. Here, we identify the common mechanisms underlying both intrinsic and acquired resistance that are induced by doxorubicin, the main cytotoxic component of R-CHOP. We performed global transcriptomic analysis of (1) a panel of resistant versus sensitive and (2) isogenic acquired doxorubicin-resistant DLBCL cell lines following short and chronic exposure to doxorubicin respectively. Doxorubicin-induced stress in resistant cells activates a distinct transcriptional signature that is enriched in metabolic reprogramming and oncogenic signalling. Selective and sustained activation of non-canonical NF-κB signalling in these resistant cells exacerbated their survival by augmenting glycolysis. In response to doxorubicin, p52-RelB complexes transcriptionally activated multiple glycolytic regulators with prognostic significance through increased recruitment at their gene promoters. Targeting p52-RelB and their targets in resistant cells increased doxorubicin sensitivity in vitro and in vivo. Collectively, our study uncovered novel molecular drivers of doxorubicin-induced resistance that are regulated by non-canonical NF-κB pathway. We reveal new avenues of therapeutic targeting for R-CHOP-treated refractory/relapsed DLBCL patients. Nanyang Technological University National Medical Research Council (NMRC) National Research Foundation (NRF) Submitted/Accepted version This study is funded by the National Research Foundation (NRF) Singapore, under its Singapore NRF Fellowship (NRFNRFF2018-04). In addition, we thank the Nanyang Assistant Professorship (NAP) Startup-grant to Y.L. lab and National Medical Research Council (NMRC-OFLCG18May0028), Tanoto Foundation and Ling Foundation for their support.

ObjectiveTo date, there are no predictive biomarkers to guide selection of patients with gastric cancer (GC) who benefit from paclitaxel. Stomach cancer Adjuvant Multi-Institutional group Trial (SAMIT) was a 2×2 factorial randomised phase III study in which patients with GC were randomised to Pac-S-1 (paclitaxel +S-1), Pac-UFT (paclitaxel +UFT), S-1 alone or UFT alone after curative surgery.DesignThe primary objective of this study was to identify a gene signature that predicts survival benefit from paclitaxel chemotherapy in GC patients. SAMIT GC samples were profiled using a customised 476 gene NanoString panel. A random forest machine-learning model was applied on the NanoString profiles to develop a gene signature. An independent cohort of metastatic patients with GC treated with paclitaxel and ramucirumab (Pac-Ram) served as an external validation cohort.ResultsFrom the SAMIT trial 499 samples were analysed in this study. From the Pac-S-1 training cohort, the random forest model generated a 19-gene signature assigning patients to two groups: Pac-Sensitive and Pac-Resistant. In the Pac-UFT validation cohort, Pac-Sensitive patients exhibited a significant improvement in disease free survival (DFS): 3-year DFS 66% vs 40% (HR 0.44, p=0.0029). There was no survival difference between Pac-Sensitive and Pac-Resistant in the UFT or S-1 alone arms, test of interaction pConclusionUsing machine-learning techniques on one of the largest GC trials (SAMIT), we identify a gene signature representing the first predictive biomarker for paclitaxel benefit.Trial registration numberUMIN Clinical Trials Registry: C000000082 (SAMIT); ClinicalTrials.gov identifier, 02628951 (South Korean trial)

Supplementary methods. Supplementary Figure 1. Phenotyping of B-cells in non-malignant tissues. A, Quantitation of marker positivity across ten tonsil and two reactive lymph node samples (rLN). Analysis is spatially resolved between the GC and extra-GC zones. B, Spatial map of cellular coordinates based on cell segmentation of images in Figure 1B. Marker-positivity is indicated, and a total proportion of positive and negative cells is depicted as a pie chart. These maps were used to derive sub-population phenotypes depicted in Figure 1C. Scale bar is 100μm. C, Proliferation analysis (i.e., Ki67-positivity) among sub-populations in five tonsil samples. Median with interquartile range, whiskers denote 10th and 90th percentile. Supplementary figure 2. Example pseudo-colored mfIHC images for MYC, BCL2, BCL6 cases in DLBCL. Images of a range of mean fluorescent intensities are shown with equal scaling for reference. Supplementary figure 3. Global distribution of MYC, BCL2 and BCL6 sub-populations within DLBCL cohorts. Heat-maps displaying the percentage extent of individual markers and each sub-population within the DLBCL NUH, CMMC, SGH and MDA cohorts. Hierarchical k-means clustering of patients according to sub-population extent is applied. Positivity shading for single markers ranges between 0-100% positivity, whereas shading for sub-populations reflects 0-50% positivity and remains fully saturated until 100%. IPI Risk Group - International Prognostic Index Risk Group, FISH - fluorescence in situ hybridization. Supplementary figure 4. Intra-tumor heterogeneity of sub-populations. A, Correlation of sub-population extent quantification between two biopsies of the same patient for which at least two tissue microarray (TMA) biopsies are available. Correlation is shown separately for lymph node and extranodal biopsies. Spearman rho is indicated for each correlation. Axes are in exponential and equivalent in all panels. B, Sub-population percentage extent quantification across multiple TMA cores (columns) of the same patient (rows). Pie charts are ordered according to decreasing cell numbers evaluated per core. All patients from the NUH cohort with at least five cores are evaluated. A heterogenous cluster is highlighted by the red box. Supplementary figure 5. Spatial heterogeneity of sub-population interactions. A, Conceptual schematic of pair correlation function (PCF) plots depicting a clustered distribution (left, green) and a random distribution (right, grey). Representative counterpart spatial maps are above each plot. B, PCF analysis for sub-populations to investigate spatial clustering (top). Mean results for two independent cohorts (shading is cohort standard deviation). An example tissue microarray core is shown as physical distance reference for spatial analyses (bottom left). Absolute number of neighboring cells expected within a given radius (data from 3500 randomly selected cells across all images, mean with standard deviation) (bottom right). C, Actual spatial map of sub-populations of an example DLBCL case (top). Extent of all sub-populations within the sample is shown on the left. Simulated, hypothetical random distribution of cells for the same case (middle). PCF analysis for the shown sample and its matched simulated random distribution (bottom). Scale bars in B and C are 100µm. D, Mean deviations from expected neighbor abundance (Δ%) summarizing cell-cell interactions between sub-populations for the sample shown in (C). E, Sub-population interaction matrices from spatially distinct biopsies (cores in tissue microarray) for example DLBCL patients. Biopsies of stable, spatially homogenous, sub-population interaction profiles are grouped (top), whereas biopsies of a differing, heterogenous, interaction profile are grouped separately (bottom). Supplementary figure 6. Global deviations from expected spatial neighbor abundance (Δ%). Hierarchical clustering (minimum variance method) of measured Δ% for all cases in the SGH and MDA cohorts. Extents of sub-populations are indicated for reference (top). For the MDA cohort, multiple biopsies (n = 1-3) from the same patient were included in the analysis to determine spatial interaction similarity across spatially distinct regions (bottom). Supplementary figure 7. Correlation of predicted MYC, BCL2 and BCL6 sub-population percentage extent based on single oncogene positivity and observed percentage extent in DLBCL cohorts. Spearman rho, axes are equivalent in all panels. Supplementary figure 8. Variance of M+2+6- percentage extent in the context of positivity calling across a 15% cut-off. A, M+2+6- scoring variance across multiple pathological imaging fields. All whole-tissue DLBCL sections from University of Palermo (UP), and samples from the NUH TMA with at least four fields scored per patient and a mean M+2+6- score above 5% are shown. Mean with SD. Ordinates between 50-100% are compressed for clarity. Dashed line denotes M+2+6- 15% positivity. B, Stability of M+2+6- case positivity calling across scoring increasing number of imaging fields. All cases from panel A with at least five fields scored in this study are shown. Only one case is called M+2+6- Low (

Cancers often overexpress multiple clinically relevant oncogenes, but it is not known if combinations of oncogenes in cellular subpopulations within a cancer influence clinical outcomes. Using quantitative multispectral imaging of the prognostically relevant oncogenes MYC, BCL2, and BCL6 in diffuse large B-cell lymphoma (DLBCL), we show that the percentage of cells with a unique combination MYC+BCL2+BCL6− (M+2+6−) consistently predicts survival across four independent cohorts (n = 449), an effect not observed with other combinations including M+2+6+. We show that the M+2+6− percentage can be mathematically derived from quantitative measurements of the individual oncogenes and correlates with survival in IHC (n = 316) and gene expression (n = 2,521) datasets. Comparative bulk/single-cell transcriptomic analyses of DLBCL samples and MYC/BCL2/BCL6-transformed primary B cells identify molecular features, including cyclin D2 and PI3K/AKT as candidate regulators of M+2+6− unfavorable biology. Similar analyses evaluating oncogenic combinations at single-cell resolution in other cancers may facilitate an understanding of cancer evolution and therapy resistance.Significance:Using single-cell–resolved multiplexed imaging, we show that selected subpopulations of cells expressing specific combinations of oncogenes influence clinical outcomes in lymphoma. We describe a probabilistic metric for the estimation of cellular oncogenic coexpression from IHC or bulk transcriptomes, with possible implications for prognostication and therapeutic target discovery in cancer.This article is highlighted in the In This Issue feature, p. 1027

Quantitative single-cell analysis of MYC, BCL2, and BCL6 protein expression in B cells in nonmalignant tissues and diffuse large B-cell lymphoma. A, Schematic workflow of a quantitative digital pathology experiment. B, Spectrally unmixed multiplexed fluorescent images for CD20, MYC, BCL2, and BCL6 and nuclear counterstaining in tonsil tissue. The germinal center (GC) and extragerminal center (extra-GC) zones are indicated. C, Spatial map of MYC/BCL2/BCL6 subpopulations, i.e., possible permutations of MYC/BCL2/BCL6-positivity and -negativity within the CD20-positive cell population in a tonsil image. D, Quantitation of subpopulation extent within CD20-positive cells in tonsils and reactive lymph nodes resolved spatially between the GC and extra-GC zones. E, Example of pseudocolored MYC/BCL2/BCL6/CD20 mfIHC staining in diffuse large B-cell lymphoma (DLBCL; left). Cell segmentation and single oncogene positivity masks are shown within the CD20-positive cell population (right). F, Summary of percentage extent of subpopulations across patients from National University Hospital (NUH), Chi-Mei Medical Center (CMMC), MD Anderson (MDA), and Singapore General Hospital (SGH). Relevant clinicopathologic features are indicated; see also Supplementary Fig. S3. Patients were ordered arbitrarily according to extent of the triple-positive M+2+6+ subpopulation extent. IPI Risk Group, International Prognostic Index Risk Group; FISH, fluorescence in situ hybridization. G, Intrapatient spatial stability of subpopulations – proportion of subpopulations measured across four spatially distinct biopsies from the same patient (rows). Biopsy comparison overview is shown across 11 representative example DLBCL patients (columns). See also Supplementary Fig. S4A and S4B for a correlation analysis for all patients with multiple biopsies available. H, Proliferation analysis (i.e., Ki-67-positivity) among subpopulations in DLBCL samples. Proliferative BCL6-positive subpopulations are grouped. Median with interquartile range, whiskers denote 10th and 90th percentile. Mann–Whitney test (BCL6-positive vs. -negative subpopulations). All scale bars, 100 μm.

Transcriptomic analysis of M+2+6− high cases and potential role of CCND2. A, Correlation of observed M+2+6− percentage extent in the BCA cohort with the cell-of-origin (COO) DLBCL90-COO signature. Bonferroni corrected Kruskal–Wallis test for ABC vs. others. B, Correlation of M+2+6− metric in GEP cohorts with COO signatures. Mean M+2+6− metric value per group per cohort is shown. Bonferroni corrected paired-samples t test. C, Correlation of the M+2+6− percentage extent and metric evaluated by mfIHC and mRNA inference, respectively, with genetic subtypes (LymphGen classification). D, Sankey plot of M+2+6− dichotomized grouping matched with molecular features. E, Volcano plot of pooled direct correlation of gene mRNA expression and M+2+6− metric across seven GEP cohorts. Genes highly correlated with M+2+6− metric across datasets at absolute Spearman rho ≥0.2 and FDR≤0.001 are shown (see also Supplementary Table S11). The abscissa is scaled exponentially. F, Differential gene expression between primary GC B cells overexpressing M+2+ and M+2+6+ (see also Supplementary Table S12). Analysis is generated from 4 biological replicates from each condition, from cells of independent donors. G, Genes highly enriched in M+2+6− cells: correlation of results from E and F. H,CCDN2 gene expression in GEP cohorts in patients dichotomized by M+2+6− 15% metric (left) and in primary B cells (right). Paired t test (left); mean with standard deviation and FDR (FDR as per Supplementary Table S12) for t test (right). I, Single-cell RNA-seq of GC primary B cells transduced either with BCL2 and MYC (MYC-transduced) or BCL2 and BCL6 (BCL6-transduced). Untransduced GC primary B cells are also included. Expression of CCND2 is indicated in color. J, Proliferation analysis of M+2+6+ primary GC B cells overexpressing cyclin D2 (CCND2) compared with M+2+6+ primary GC B cells transduced with an empty vector (EV). Analysis performed with 3 biological replicates for each condition, using cells from 3 independent patients; mean with standard deviation; t test. UMAP, Uniform Manifold Approximation and Projection.

Multivariate analysis of continuous M+2+6− percentage extent at 5% increments as a predictor of OS in the NUH, SGH, and MDA cohorts of DLBCL (Cox proportional hazards model)

Supplementary table 1. Per-patient mfIHC MYC, BCL2 and BCL6 single oncogene and subpopulation scores for normal tonsil tissue and reactive lymph node tissue. Supplementary table 2. Per-patient mfIHC MYC, BCL2 and BCL6 single oncogene and subpopulation scores for DLBCL tissue (NUH, CMMC, SGH, MDA, BCA and UP). Supplementary table 6. Inferred percentage extents of MYC, BCL2, BCL6 and sub-population metrics in GEP cohorts. Supplementary table 11. Correlation of M+2+6- metric with gene expression in GEP cohorts. Supplementary table 12. Differential gene expression analysis of primary germinal center (GC) B-cells with M+2+ and M+2+6+ overexpression. Supplementary table 13. Differentially expressed genes between M+2+6- and all other malignant cells in scRNA-seq samples of DLBCL. Dichotomized non-parametric comparison, Wilcoxon rank sum test. Supplementary table 14. Analysis of positive enrichment of Wikipathways terms between M+2+6- and all other malignant cells in scRNA-seq samples of DLBCL by gprofiler2.

MYC, BCL2, and BCL6 protein coexpression in DLBCL can be inferred from individual marker data. A, Schematic of possible relationships between expression of three oncogenes in a population of cells. The distribution of these oncogenes can either reflect interdependent expression, independent/stochastic expression, or mutually exclusive expression. These relationships result in the percentage extent of oncogenes in the tumor being either strongly positively correlated, not correlated, or strongly negatively correlated, respectively. Created with BioRender.com. B, Correlation of MYC, BCL2, and BCL6 percentage extent across patients in DLBCL cohorts. Spearman correlation; axes are equivalent in all panels. C, Good correlation between probabilistically predicted subpopulation percentage extent based on single oncogene positivity and observed percentage extent in the NUH cohort. Cases of double-hit lymphoma (DHL, MYC+BCL2+ translocations or MYC+BCL6+ translocations) or triple-hit lymphoma (THL) are highlighted. Spearman rho for each correlation is shown; axes are equivalent in all panels. Correlation for other cohorts can be found in Supplementary Fig. S7. D, Prospective evaluation of an optimal dichotomization cutoff for M+2+6− percentage extent in the BCA cohort. Univariate Cox PH model at 1% extent positivity increment, HR for death with 95% CI. HR scale is exponential. Optimal dichotomization cutoff is highlighted in blue. E, Kaplan–Meier OS analysis of the chromogenic IHC BCA cohort evaluation stratified into M+2+6− metric high and low groups across an absolute value of 15% M+2+6−metric. Log-rank test, shading denotes 95% confidence interval. CMMC, Chi-Mei Medical Center.

Validation of prognostic significance of the M+2+6− subpopulation metric in gene-expression datasets. A, Distribution of single oncogene positivity in DLBCL cohorts as assessed by mfIHC (see Supplementary Fig. S9A and S9B). B, Impact of subpopulation metrics in GEP datasets on OS. Pooled univariate Cox PH model analysis; metric was used as a continuous variable in the model at 5% increments. HR per 5% increment with 95% CI is shown; CI are proportional on both tails but are capped at the graph's edges. Pooled P values were Bonferroni corrected to adjust for multiple testing and are shown for each subpopulation. C, Kaplan–Meier OS analysis of GEP cohorts stratified uniformly across absolute 15% M+2+6− metric into -high and -low groups. Log-rank test, shading denotes 95% CI. Total patient numbers in each group are shown. CMMC, Chi-Mei Medical Center.

Prognostic significance of subpopulations after R-CHOP therapy. A, Pooled univariate Cox PH model analysis for MYC, BCL2, and BCL6 single oncogene and subpopulations percentage extent as predictors of OS across multiple DLBCL cohorts. Percentage extent was used as a continuous variable in the model at 5% increments (see Survival Analysis) for an unbiased comparison between the variables. Pooled P values were Bonferroni corrected for single oncogenes and subpopulations independently to adjust for multiple testing and are shown for each variable. Hazard ratio (HR) with 95% confidence interval (CI) per 5%-positivity increment is shown (see also Supplementary Table S4). B, Kaplan–Meier OS analysis of dichotomized into M+2+6− high and low groups. Log-rank test, shading denotes 95% CI. An optimal dichotomization cutoff was used for stratification; total patient numbers in each group are shown.

Background Extranodal natural killer/T-cell lymphoma (NKTL) is an aggressive type of non-Hodgkin lymphoma with dismal outcome. A better understanding of disease biology and key oncogenic process is necessary for the development of targeted therapy. Super-enhancers (SEs) have been shown to drive pivotal oncogenes in various malignancies. However, the landscape of SEs and SE-associated oncogenes remain elusive in NKTL. Methods We used Nano-ChIP-seq of the active enhancer marker histone H3 lysine 27 acetylation (H3K27ac) to profile unique SEs NKTL primary tumor samples. Integrative analysis of RNA-seq and survival data further pinned down high value, novel SE oncogenes. We utilized shRNA knockdown, CRISPR-dCas9, luciferase reporter assay, ChIP-PCR to investigate the regulation of transcription factor (TF) on SE oncogenes. Multi-color immunofluorescence (mIF) staining was performed on an independent cohort of clinical samples. Various function experiments were performed to evaluate the effects of TOX2 on the malignancy of NKTL in vitro and in vivo. Results SE landscape was substantially different in NKTL samples in comparison with normal tonsils. Several SEs at key transcriptional factor (TF) genes, including TOX2, TBX21(T-bet), EOMES, RUNX2, and ID2, were identified. We confirmed that TOX2 was aberrantly overexpressed in NKTL relative to normal NK cells and high expression of TOX2 was associated with worse survival. Modulation of TOX2 expression by shRNA, CRISPR-dCas9 interference of SE function impacted on cell proliferation, survival and colony formation ability of NKTL cells. Mechanistically, we found that RUNX3 regulates TOX2 transcription by binding to the active elements of its SE. Silencing TOX2 also impaired tumor formation of NKTL cells in vivo. Metastasis-associated phosphatase PRL-3 has been identified and validated as a key downstream effector of TOX2-mediated oncogenesis. Conclusions Our integrative SE profiling strategy revealed the landscape of SEs, novel targets and insights into molecular pathogenesis of NKTL. The RUNX3-TOX2-SE-TOX2-PRL-3 regulatory pathway may represent a hallmark of NKTL biology. Targeting TOX2 could be a valuable therapeutic intervene for NKTL patients and warrants further study in clinic.

Recurrent cytogenetic abnormalities are the main hallmark of multiple myeloma (MM) and patients having 2 or more high-risk prognostic events are associated with extremely poor outcome. 17p13(del) and 1q21(gain) are critical and independent high-risk cytogenetic markers, however, the biological significance underlying the poor outcome in MM patients having co-occurrence of both these chromosomal aberrations has never been interrogated. Herein, we identified that patients harbouring concomitant 17p13(del) with 1q21(gain) demonstrated the worst prognosis as compared to patients with single- (either 17p13(del) or 1q21(gain)) and with no chromosomal events (WT for both chromosomal loci); and they are highly enriched for genomic instability (GI) signature. We discovered that the GI feature in the patients with concomitant 17p13(del)-1q21(gain) was recapitulating the biological properties of myeloma cells with co-existing p53-deficiency and NEIL1 mRNA-hyper-editing (associated with chromosome 17p and 1q, respectively) that have inherent DNA damage response (DDR) and persistent activation of Chk1 pathway. Importantly, this became a vulnerable point for therapeutic targeting whereby the cells with this co-abnormalities demonstrated hyper-sensitivity to siRNA- and pharmacological-mediated-Chk1 inhibition, as observed at both the in vitro and in vivo levels. Mechanistically, this was attributable to the synthetic lethal relationship between p53-NEIL1-Chk1 abnormalities. The Chk1 inhibitor (AZD7762) tested showed good synergism with standard-of-care myeloma drugs, velcade and melphalan, thus further reinforcing the translational potential of this therapeutic approach. In summary, combination of NEIL1-p53 abnormalities with an ensuing Chk1 activation could serve as an Achilles heel and predispose MM cells with co-existing 1q21(gain) and 17p13(del) to therapeutic vulnerability for Chk1 inhibition.

Purpose:Induction cisplatin and gemcitabine chemotherapy is a standard treatment for locally advanced nasopharyngeal carcinoma (NPC). Inhibition of VEGF axis has been shown to promote maturation of microvasculature and improve perfusion. We conducted a four-arm study to assess the effect of two doses of either sunitinib or bevacizumab with chemotherapy in NPC.Patients and Methods:Patients with treatment-naïve locally advanced NPC were treated with three cycles of 3-weekly cisplatin and gemcitabine preceded by 1 week of anti-VEGF therapy for each cycle, followed by standard concurrent chemoradiation: arm A patients received 7 days of 12.5 mg/day sunitinib; arm B 7 days of 25 mg/day sunitinib; arm C bevacizumab 7.5 mg/kg infusion; arm D bevacizumab 2.5 mg/kg infusion. Patients with metastatic NPC were treated with up to six cycles of similar treatment without concurrent chemoradiation.Results:Complete metabolic response (mCR) by whole body 18FDG PET was highest in arm C (significant difference in four groups Fisher exact test P = 0.001; type 1 error = 0.05), with 42% mCR (95% confidence interval, 18–67) and 3-year relapse-free survival of 88% in patients with locally advanced NPC. Significant increase in pericyte coverage signifying microvascular maturation and increased immune cell infiltration was observed in posttreatment tumor biopsies in Arm C. Myelosuppression was more profound in sunitinib containing arms, and tolerability was established in arm C where hypertension was the most significant toxicity.Conclusions:Bevacizumab 7.5 mg/kg with cisplatin and gemcitabine was well tolerated. Promising tumor response was observed and supported mechanistically by positive effects on tumor perfusion and immune cell trafficking into the tumor.

Figure S1- Study schema Figure S2 - Example of complete metabolic response after 3 cycles of induction therapy in a representative Arm C patient treated with bevacizumab at 7.5mg/kg in combination with cisplatin and gemcitabine. Figure S3- Relapse free survival (RFS) in months by study arms of patients with locally advanced disease who underwent concurrent chemoradiation after induction chemotherapy. Figure S4 - Relapse free survival in months by metabolic response to induction therapy. Figure S5 - (A) Spaghetti Plot of EBV viral load at baseline (BL), C2D1 and C3D1; (B)Circulating VEGF levels in plasma samples collected at BL, C1D1, C2D1 and end of induction therapy, EOT. Figure 6a- Figure S6 - Induction of mature blood vessel in the NPC tumour microenvironment 7 days following initiation of sunitinib and bevacizumab exposure. Figure S6b - Quantification of blood vessel densities Figure S7- Immune cell infiltration in the NPC tumour microenvironment 7 days following initiation of sunitinib or bevacizumab exposure

Supplementary methods and supplementary tables

BackgroundMacrophages are abundant immune cells in the microenvironment of diffuse large B-cell lymphoma (DLBCL). Conventional immunohistochemistry-based studies with varying prognostic significance precludes a comprehensive analysis of macrophage subtypes in DLBCL. We hypothesized that whole-transcriptomic analysis (WTA) of macrophage in-situ would identify new macrophage subsets of biological and clinical significances.MethodsDigital spatial profiling with WTA of CD68+ cells was performed in 47 DLBCL and 17 reactive lymphoid tissues (RLTs), to define macrophage signatures (termed “MacroSigs”) of distinct lymphoid spatial niches and clinical scenarios. Eight independent DLBCL datasets (4,594 patients) with transcriptomic and survival information were used for validation of MacroSigs.ResultsDigital spatial profiling revealed previously unrecognized transcriptomic differences between macrophages populating distinct spatial compartments in RLTs (light zone (LZ)/ dark zone (DZ), germinal center (GC)/ interfollicular (IF) regions), and in between disease states (RLTs and DLBCL with or without relapsed disease). This transcriptomic diversity of macrophages was categorized into eight MacroSigs. Spatial-MacroSigs associate with specific cell-of-origin (COO) subtypes of DLBCL, of particular interest being the IF-MacroSig enriched in the unclassified COO (PPPConclusionsThis study first provides spatially-resolved macrophage WTA in reactive and malignant lymphoid tissues. Gene expression signatures of macrophages in the DZ and relapsed-DLBCL samples are consistently prognostic in multiple datasets and offer insights into novel therapeutic strategies for DLBCL.

Although combination therapy is the standard of care for relapsed/refractory non-Hodgkin’s lymphoma (RR-NHL), combination treatment chosen for an individual patient is empirical, and response rates remain poor in individuals with chemotherapy-resistant disease. Here, we evaluate an experimental-analytic method, quadratic phenotypic optimization platform (QPOP), for prediction of patient-specific drug combination efficacy from a limited quantity of biopsied tumor samples. In this prospective study, we enrolled 71 patients with RR-NHL (39 B cell NHL and 32 NK/T cell NHL) with a median of two prior lines of treatment, at two academic hospitals in Singapore from November 2017 to August 2021. Fresh biopsies underwent ex vivo testing using a panel of 12 drugs with known efficacy against NHL to identify effective single and combination treatments. Individualized QPOP reports were generated for 67 of 75 patient samples, with a median turnaround time of 6 days from sample collection to report generation. Doublet drug combinations containing copanlisib or romidepsin were most effective against B cell NHL and NK/T cell NHL samples, respectively. Off-label QPOP-guided therapy offered at physician discretion in the absence of standard options ( n = 17) resulted in five complete responses. Among patients with more than two prior lines of therapy, the rates of progressive disease were lower with QPOP-guided treatments than with conventional chemotherapy. Overall, this study shows that the identification of patient-specific drug combinations through ex vivo analysis was achievable for RR-NHL in a clinically applicable time frame. These data provide the basis for a prospective clinical trial evaluating ex vivo–guided combination therapy in RR-NHL.

ObjectivesEpigenomic alterations in cancer interact with the immune microenvironment to dictate tumour evolution and therapeutic response. We aimed to study the regulation of the tumour immune microenvironment through epigenetic alternate promoter use in gastric cancer and to expand our findings to other gastrointestinal tumours.DesignAlternate promoter burden (APB) was quantified using a novel bioinformatic algorithm (proActiv) to infer promoter activity from short-read RNA sequencing and samples categorised into APBhigh, APBint and APBlow. Single-cell RNA sequencing was performed to analyse the intratumour immune microenvironment. A humanised mouse cancer in vivo model was used to explore dynamic temporal interactions between tumour kinetics, alternate promoter usage and the human immune system. Multiple cohorts of gastrointestinal tumours treated with immunotherapy were assessed for correlation between APB and treatment outcomes.ResultsAPBhigh gastric cancer tumours expressed decreased levels of T-cell cytolytic activity and exhibited signatures of immune depletion. Single-cell RNAsequencing analysis confirmed distinct immunological populations and lower T-cell proportions in APBhigh tumours. Functional in vivo studies using ‘humanised mice’ harbouring an active human immune system revealed distinct temporal relationships between APB and tumour growth, with APBhigh tumours having almost no human T-cell infiltration. Analysis of immunotherapy-treated patients with GI cancer confirmed resistance of APBhigh tumours to immune checkpoint inhibition. APBhigh gastric cancer exhibited significantly poorer progression-free survival compared with APBlow (median 55 days vs 121 days, HR 0.40, 95% CI 0.18 to 0.93, p=0.032).ConclusionThese findings demonstrate an association between alternate promoter use and the tumour microenvironment, leading to immune evasion and immunotherapy resistance.

Primary Epstein-Barr virus (EBV)-positive nodal T/NK-cell lymphoma (PTCL-EBV) is a poorly understood disease which shows features resembling extranodal NK/T-cell lymphoma (ENKTL) and is currently not recognized as a distinct entity but categorized as a variant of primary T-cell lymphoma not otherwise specified (PTCL-NOS). Herein, we analyzed copynumber aberrations (n=77) with a focus on global measures of genomic instability and homologous recombination deficiency and performed gene expression (n=84) and EBV miRNA expression (n=24) profiling as well as targeted mutational analysis (n=16) to further characterize PTCL-EBV in relation to ENKTL and PTCL-NOS. Multivariate analysis revealed that patients with PTCL-EBV had a significantly worse outcome compared to patients with PTCL-NOS (P=0.002) but not to those with ENKTL. Remarkably, PTCL-EBV exhibited significantly lower genomic instability and homologous recombination deficiency scores compared to ENKTL and PTCL-NOS. Gene set enrichment analysis revealed that many immune-related pathways, interferon α/γ response, and IL6_JAK_STAT3 signaling were significantly upregulated in PTCLEBV and correlated with lower genomic instability scores. We also identified that NFκB-associated genes, BIRC3, NFKB1 (P50) and CD27, and their proteins are upregulated in PTCL-EBV. Most PTCL-EBV demonstrated a type 2 EBV latency pattern and, strikingly, exhibited downregulated expression of most EBV miRNA compared to ENKTL and their target genes were also enriched in immune-related pathways. PTCL-EBV also showed frequent mutations of TET2, PIK3CD and STAT3, and are characterized by microsatellite stability. Overall, poor outcome, low genomic instability, upregulation of immune pathways and downregulation of EBV miRNA are distinctive features of PTCL-EBV. Our data support the concept that PTCL-EBV could be considered as a distinct entity, provide novel insights into the pathogenesis of the disease and offer potential new therapeutic targets for this tumor.

Objective Pathogenic variations in the homologous recombination (HR) gene, BRCA1 interacting protein C-terminal helicase 1 (BRIP1) increase the risk for ovarian cancer. PARP inhibitors (PARPi) exert a synthetic lethal effect in BRCA-mutated ovarian cancers. Effective HR requires cooperation between BRCA1 and BRIP1; therefore, BRIP1-incompetancy may predict vulnerability to synthetic lethality. Here we investigated the response of ovarian epithelial cells with defective BRIP1 function to PARPi, and compared these cells to those lacking BRCA1 activity. Methods We engineered Chinese Hamster ovarian (CHO) epithelial cells to express deficient BRIP1 or BRCA1, and exposed them to olaparib with or without carboplatin or cisplatin. We assessed cellular proliferation and survival; we calculated inhibitory concentrations and combination and reduction drug indices. Results BRIP1 and BRCA1 inactivation impedes HR activity, decreases cellular proliferation and compromises DNA damage recovery. Platinum agent exposure impairs cellular survival. Olaparib exposure alone decreases cell viability in BRCA1-deficient cells, although has no effect on BRIP1-deficient cells. Combining carboplatin or cisplatin with olaparib synergistically attenuates cellular survival, consistent with synthetic lethality. Conclusions BRIP1-deficient ovarian epithelial cells exhibit defective HR, resulting in synthetic lethality when exposed to a platinum agent/PARPi combination. PARPi alone had no effect; this lack of effect may result from distinguishing molecular properties of BRIP1and/or consequences of genomic background. Our study identifies altered BRIP1 as a target for precision medicine-based therapies for ovarian cancers. This investigation supports consideration of the use of a platinum agent/PARPi combination in ovarian cancers depending upon genetic profile and genomic background.

PRDM (PRDI-BF1 and RIZ homology domain containing) family members are sequence-specific transcriptional regulators involved in cell identity and fate determination, often dysregulated in cancer. The PRDM15 gene is of particular interest, given its low expression in adult tissues and its overexpression in B-cell lymphomas. Despite its well characterized role in stem cell biology and during early development, the role of PRDM15 in cancer remains obscure. Herein, we demonstrate that while PRDM15 is largely dispensable for mouse adult somatic cell homeostasis in vivo, it plays a critical role in B-cell lymphomagenesis. Mechanistically, PRDM15 regulates a transcriptional program that sustains the activity of the PI3K/AKT/mTOR pathway and glycolysis in B-cell lymphomas. Abrogation of PRDM15 induces a metabolic crisis and selective death of lymphoma cells. Collectively, our data demonstrate that PRDM15 fuels the metabolic requirement of B-cell lymphomas and validate it as an attractive and previously unrecognized target in oncology., The transcriptional regulator PRDM15 is expressed at low levels in normal tissues but overexpressed in B-cell lymphomas. Here, the authors show that PRDM15 depletion does not affect adult somatic cell homeostasis but leads to a metabolic crisis which impairs B-cell lymphomagenesis.

4026 Background: Immune checkpoint inhibitors (ICI) are now standard-of-care treatment for patients with metastatic gastric cancer (GC). To guide patient selection for ICI therapy, programmed death ligand-1 (PD-L1) biomarker expression is routinely assessed via immunohistochemistry (IHC). Regulatory approval for ICIs is granted based on PD-L1 expression status, scored using metrics such as the combined positive score (CPS). However, with an increasing number of approved ICIs, each paired with a different PD-L1 antibody IHC assay used in their respective landmark trials, there is an unmet clinical and logistical need for harmonization. We thus investigated the interchangeability between the Dako 22C3, Dako 28-8 and Ventana SP-142 assays in GC PD-L1 IHC. Methods: In this cross-sectional study, samples were obtained via biopsy or resection of gastric cancer at the National University Hospital, Singapore. We scored 362 GC samples for PD-L1 CPS, tumor proportion score (TPS) and immune cells (IC) using a multiplex immunohistochemistry/immunofluorescence technique. 344 samples were developed into a tissue microarray (TMA), while 18 samples were used as whole slides for orthogonal validation. The samples selected for whole slide analysis were obtained from GC patients treated with ICI therapy. Results: The percentage of PD-L1 positive samples at clinically relevant CPS ≥1, ≥5 and ≥10 cut-offs (Table) for the 28-8 assay were approximately two-fold higher than that of the 22C3 (CPS≥1: 70.3% vs 49.4%, p

One common cause of vision loss after retinal detachment surgery is the formation of proliferative and contractile fibrocellular membranes. This aberrant wound healing process is mediated by epithelial-mesenchymal transition (EMT) and hyper-proliferation of retinal pigment epithelial (RPE) cells. Current treatment relies primarily on surgical removal of these membranes. Here, we demonstrate that a bio-functional polymer by itself is able to prevent retinal scarring in an experimental rabbit model of proliferative vitreoretinopathy. This is mediated primarily via clathrin-dependent internalisation of polymeric micelles, downstream suppression of canonical EMT transcription factors, reduction of RPE cell hyper-proliferation and migration. Nuclear factor erythroid 2–related factor 2 signalling pathway was identified in a genome-wide transcriptomic profiling as a key sensor and effector. This study highlights the potential of using synthetic bio-functional polymer to modulate RPE cellular behaviour and offers a potential therapy for retinal scarring prevention.

The implementation of clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 systems in mammalian cells has sparked an exciting new era in targeted gene editing. CRISPR-Cas9 technologies allow gene function to be interrogated by gene deletions, mutations, and truncations, and by epitope tagging and promoter activity modulation. Many robust protocols have been published to date on CRISPR-Cas9 techniques, however, most of these focus on adherent cell lines. Suspension cell lines, typically of hematolymphoid origin, such as Jurkat, Daudi, and TOLEDO, pose unique challenges to the setup of CRISPR experiments. Here, using B cell lymphoma cells as a primary model, we describe a comprehensive protocol for targeted gene manipulations using the CRISPR-Cas9 system in suspension cells. We also highlight necessary optimization steps to make this approach universal to other suspension cell lines. We first describe a detailed protocol for transient expression of the Cas9 nuclease and guide RNAs. We then suggest workflows for obtaining single-cell clones and for screening for successful homozygous knockout (KO) clones in suspension lines. This protocol aims to serve as a comprehensive resource to facilitate gene editing experiments for users starting CRISPR-Cas9 gene editing protocols on suspension cell lines or those looking to optimize their current workflows. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Transient CRISPR Cas9-gRNA delivery for gene knockout by NeonTM electroporation Support Protocol 1: Designing and preparing gene-specific gRNA Support Protocol 2: Preparation of conditioned medium and culture vessels for single-cell FACS Alternate Protocol 1: Transient CRISPR Cas9-gRNA delivery for gene knockout by Nepagene electroporator Basic Protocol 2: FACS and single-cell clone generation Alternate Protocol 2: Manual cell dilution to obtain single-cell clones Basic Protocol 3: Confirming indels status in single-cell clones by PCR on genomic DNA and Sanger sequencing.

Background: Previous studies in Western populations, using immunohistochemistry (IHC) methods to subtype diffuse large B-cell lymphoma (DLBCL), suggest that germinal center B-cell lymphomas (GCBs) have improved outcomes. However, data in Asians have been limited and conflicting. This study aims to evaluate the prognostic impact of cell-of-origin (COO) subtyping by IHC and Lymph2Cx in South-East Asian (SEA) DLBCL patients, and to summarize the existing literature.Methods: A single-center retrospective analysis of 384 DLBCL patients diagnosed 2013-2018 who received Rituximab-based chemotherapy was performed. Hans and Lymph2Cx were used to assign COO and correlated with outcomes.Results: International Prognostic Index (IPI) score was associated with overall survival (OS) and progression-free survival (PFS). The 5-yr-OS for non-GCB versus GCB for COO by Hans was 70% versus 71% p=0.39, while 5-yr-OS for ABC versus GCB for COO by Lymph2Cx was 74% versus 92% p=0.19. The 5-yr-PFS for non-GCB versus GCB for COO by Hans was 65% versus 70% p=0.26, while 5-yr-PFS for ABC versus GCB for COO by Lymph2Cx was 64% versus 86% p=0.07.Conclusions: IPI is reaffirmed to be relevant in the rituximab era. COO by Hans has no prognostic significance, while subtyping by Lymph2Cx trends toward GCBs having better PFS and OS.

The scientific and clinical communities have both experienced several harsh lessons on clinical care management and drug development during the COVID-19 pandemic. Here, we discuss several key lessons learned and describe a framework within which our two communities can work together and invest in to improve future pandemic responses.

Inhibitors of the mitotic kinase PLK1 yield objective responses in a subset of refractory cancers. However, PLK1 overexpression in cancer does not correlate with drug sensitivity, and the clinical development of PLK1 inhibitors has been hampered by the lack of patient selection marker. Using a high-throughput chemical screen, we discovered that cells deficient for the tumor suppressor ARID1A are highly sensitive to PLK1 inhibition. Interestingly this sensitivity was unrelated to canonical functions of PLK1 in mediating G2/M cell cycle transition. Instead, a whole-genome CRISPR screen revealed PLK1 inhibitor sensitivity in ARID1A deficient cells to be dependent on the mitochondrial translation machinery. We find that ARID1A knock-out (KO) cells have an unusual mitochondrial phenotype with aberrant biogenesis, increased oxygen consumption/expression of oxidative phosphorylation genes, but without increased ATP production. Using expansion microscopy and biochemical fractionation, we see that a subset of PLK1 localizes to the mitochondria in interphase cells. Inhibition of PLK1 in ARID1A KO cells further uncouples oxygen consumption from ATP production, with subsequent membrane depolarization and apoptosis. Knockdown of specific subunits of the mitochondrial ribosome reverses PLK1-inhibitor induced apoptosis in ARID1A deficient cells, confirming specificity of the phenotype. Together, these findings highlight a novel interphase role for PLK1 in maintaining mitochondrial fitness under metabolic stress, and a strategy for therapeutic use of PLK1 inhibitors. To translate these findings, we describe a quantitative microscopy assay for assessment of ARID1A protein loss, which could offer a novel patient selection strategy for the clinical development of PLK1 inhibitors in cancer.

Inhibitors of the mitotic kinase PLK1 yield objective responses in a subset of refractory cancers. However, PLK1 overexpression in cancer does not correlate with drug sensitivity, and the clinical development of PLK1 inhibitors has been hampered by the lack of patient selection marker. Using a high-throughput chemical screen, we discovered that cells deficient for the tumor suppressor ARID1A are highly sensitive to PLK1 inhibition. Interestingly this sensitivity was unrelated to canonical functions of PLK1 in mediating G2-M cell cycle transition. Instead, a whole-genome CRISPR screen revealed PLK1 inhibitor sensitivity in ARID1A deficient cells to be dependent on the mitochondrial translation machinery. We find that ARID1A knocked-out (KO) cells have an unusual mitochondrial phenotype with aberrant biogenesis, increased oxygen consumption/ expression of oxidative phosphorylation genes, but without increased ATP production. Using expansion microscopy and biochemical fractionation, we see that a subset of PLK1 localizes to the mitochondria in interphase cells. Inhibition of PLK1 in ARID1A KO cells further uncouples oxygen consumption from ATP production, with subsequent membrane depolarization and apoptosis. Knockdown of a key subunit of the mitochondrial ribosome reverses PLK1-inhibitor induced apoptosis in ARID1A deficient cells, confirming specificity of the phenotype. Together, these findings highlight a novel interphase role for PLK1 in maintaining mitochondrial fitness under metabolic stress, and a strategy for therapeutic use of PLK1 inhibitors. To translate these findings, we describe a quantitative microscopy assay for assessment of ARID1A protein loss, which could offer a novel patient selection strategy for the clinical development of PLK1 inhibitors in cancer.Statement of significanceCurrently, no predictive biomarkers have been identified for PLK1 inhibitors in cancer treatment. We show that ARID1A loss sensitizes cells to PLK1 inhibitors through a previously unrecognized vulnerability in mitochondrial oxygen metabolism.

The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently affecting millions of lives worldwide. Large retrospective studies indicate that an elevated level of inflammatory cytokines and pro-inflammatory factors are associated with both increased disease severity and mortality. Here, using multidimensional epigenetic, transcriptional, in vitro, and in vivo analyses, we report that topoisomerase 1 (TOP1) inhibition suppresses lethal inflammation induced by SARS-CoV-2. Therapeutic treatment with two doses of topotecan (TPT), an FDA-approved TOP1 inhibitor, suppresses infection-induced inflammation in hamsters. TPT treatment as late as 4 days post-infection reduces morbidity and rescues mortality in a transgenic mouse model. These results support the potential of TOP1 inhibition as an effective host-directed therapy against severe SARS-CoV-2 infection. TPT and its derivatives are inexpensive clinical-grade inhibitors available in most countries. Clinical trials are needed to evaluate the efficacy of repurposing TOP1 inhibitors for severe coronavirus disease 2019 (COVID-19) in humans., Graphical abstract, Inhibition of topoisomerase 1 through the FDA-approved molecule topotecan suppresses SARS-CoV-2-infection-associated lethal inflammation in hamster and mouse models without compromising antiviral immune responses.

Advances in next-generation sequencing technologies have led to the development of personalized genomic profiles in diagnostic panels that inform oncologists of alterations in clinically relevant genes. While targeted therapies for some alterations may be found, an effective therapeutic strategy should consider multiple and dependent genetic interactions that affect cancer progression, a task which remains challenging. There are ongoing efforts to profile cancer cells in-vitro, both to catalog their genomic information and study their sensitivity to various drugs. There is a need for tools that can interpret the personalized genomic profile of a patient in light of information from these biological and pre-clinical studies and recommend potentially useful drugs. To address this need, we develop a new algorithmic framework called DruID, to effectively combine drug efficacy predictions from a deep neural network model with information, such as drug sensitivity, drug-drug interactions and genetic dependencies, from multiple publicly available databases. We empirically evaluate DruID on cancer cell line data on which efficacy of many drugs have been experimentally determined. We find that DruID outperforms competing approaches and promises to be a useful tool in clinical decision-making.

Early relapse after platinum chemotherapy in epithelial ovarian cancer (EOC) portends poor survival. A‐priori identification of platinum resistance is therefore crucial to improve on standard first‐line carboplatin–paclitaxel treatment. The DNA repair pathway homologous recombination (HR) repairs platinum‐induced damage, and the HR recombinase RAD51 is overexpressed in cancer. We therefore designed a REMARK‐compliant study of pre‐treatment RAD51 expression in EOC, using fluorescent quantitative immunohistochemistry (qIHC) to overcome challenges in quantitation of protein expression in situ. In a discovery cohort (n = 284), RAD51‐High tumours had shorter progression‐free and overall survival compared to RAD51‐Low cases in univariate and multivariate analyses. The association of RAD51 with relapse/survival was validated in a carboplatin monotherapy SCOTROC4 clinical trial cohort (n = 264) and was predominantly noted in HR‐proficient cancers (Myriad HRDscore, Quantitative immunohistochemistry (qIHC) reveals that high expression of the DNA repair protein RAD51 in epithelial ovarian cancer (EOC) is associated with early relapse after platinum chemotherapy, and also with decreased cytotoxic T‐cell infiltration into tumors.

A dose of 200 mg 3-weekly of pembrolizumab was approved by the Food and Drug Administration (FDA) as treatment for advanced non-small cell lung cancer (NSCLC) without oncogenic drivers. This is despite evidence showing no difference in efficacy with 2 mg/kg. Our study aimed to assess the efficacy of a lower fixed dose of 100 mg, which is closer to 2 mg/kg weight-based dose in an average-sized Asian patient. All patients receiving pembrolizumab for advanced NSCLC from January 2016 to March 2020 in National University Hospital, Singapore, were included in this retrospective observational study. The effect of pembrolizumab 100 mg (Pem100) vs 200 mg (Pem200) upon survival outcomes, toxicity and cost were examined. One hundred fourteen patients received pembrolizumab. Sixty-five (57%) and 49 (43%) received Pem100 and Pem200, respectively. There was no difference in progression-free survival (PFS) and overall survival (OS) between Pem100 vs Pem200 as a single agent (PFS: 6.8 vs 4.2 months, hazard ratio [HR] 0.72, 95% confidence interval [CI] 0.36-1.46, P = .36; 9 month OS: 58% vs 63%, HR 1.08, 95% CI 0.48-2.41, P = .86) and when combined with chemotherapy (9-month PFS: 60% vs 50%, HR0.84, 95% CI 0.34-2.08, P = .71; 9-month OS: 85% vs 58%, HR 0.27, 95% CI 0.062-1.20, P = .09). No significant difference in response rate or ≥G3 immune-related toxicities between Pem100 and Pem200 was observed. A cost minimisation analysis evaluating the degree of cost savings related to drug costs estimated a within study cost saving of SGD4,290,912 and cost saving per patient of SGD39,942 in the Pem100 group. A 100 mg of pembrolizumab appears to be effective with reduction in cost. A randomised trial should be done to investigate a lower dose of pembrolizumab.

SUMMARYThe ongoing pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is currently affecting millions of lives worldwide. Large retrospective studies indicate that an elevated level of inflammatory cytokines and pro-inflammatory factors are associated with both increased disease severity and mortality. Here, using multidimensional epigenetic, transcriptional, in vitro and in vivo analyses, we report that Topoisomerase 1 (Top1) inhibition suppresses lethal inflammation induced by SARS-CoV-2. Therapeutic treatment with two doses of Topotecan (TPT), a FDA-approved Top1 inhibitor, suppresses infection-induced inflammation in hamsters. TPT treatment as late as four days post-infection reduces morbidity and rescues mortality in a transgenic mouse model. These results support the potential of Top1 inhibition as an effective host-directed therapy against severe SARS-CoV-2 infection. TPT and its derivatives are inexpensive clinical-grade inhibitors available in most countries. Clinical trials are needed to evaluate the efficacy of repurposing Top1 inhibitors for COVID-19 in humans.

BackgroundDifferentiating between malignant and normal cells within tissue samples is vital for molecular profiling of cancer using advances in genomics and transcriptomics. Cell-surface markers of tumour–normal discrimination have additional value in terms of translatability to diagnostic and therapeutic strategies. In gastric cancer (GC), previous studies have identified individual genes or proteins that are upregulated in cancer. However, a systematic analysis of cell-surface markers and development of a composite panel involving multiple candidates to differentiate tumour from normal has not been previously reported.MethodsWhole transcriptome sequencing (WTS) of GC and matched normal samples from the Singapore Gastric Cancer Consortium (SGCC) was used as a discovery cohort to identify upregulated putative cell-surface proteins. Matched WTS data from the The Cancer Genome Atlas (TCGA) was used as a validation cohort. Promising candidates from this analysis were validated orthogonally using multispectral immunohistochemistry (mIHC) with automated quantitative analysis using the Vectra platform. mIHC was performed on a tissue microarray containing matched normal, marginal and tumour tissues. The receiver-operating characteristic (ROC) curves were analysed to identify markers with the highest diagnostic validity independently and in combination.ResultsAnalysis of putative membrane protein transcripts from the SGCC discovery cohort WTS data (n=15 matched tumour and normal pairs) identified several differentially and highly expressed candidates in tumour compared with normal tissues. After validation with TCGA data (n=29 matched tumour and normal pairs), the following proteins were selected for mIHC analysis: CEACAM5, CEACAM6, CLDN4, CLDN7, and EpCAM. These were compared with established glycoprotein markers in GC, namely CA19-9 and CA72-4. Individual ROC curves yielded the best performance for CEACAM5 (area under the ROC curve (AUC)=0.80), CEACAM6 (AUC=0.82), EpCAM (AUC=0.83), and CA72-4 (AUC=0.76). Combined multiplexed imaging of these four markers revealed improved specificity and sensitivity for detection of tumour from normal tissue (AUC of 4-plex=0.91).ConclusionCEAMCAM5, CEACAM6, EpCAM, and CA72-4 form a versatile set of markers for robust discrimination of GC from adjacent normal tissue. As cell-surface markers, they are compatible with both IHC and live imaging approaches. These candidates may be exploited to improve automated identification of tumour tissue in GC.

A Synthetic Lethal (SL) interaction is a functional relationship between two genes or functional entities where the loss of either entity is viable but the loss of both is lethal. Such pairs can be used to develop targeted anticancer therapies with fewer side effects and reduced overtreatment. However, finding clinically actionable SL interactions remains challenging. Leveraging unified gene expression data of both disease-free and cancerous samples, we design a new technique based on statistical hypothesis testing, called ASTER, to identify SL pairs. We empirically find that the patterns of mutually exclusivity ASTER finds using genomic and transcriptomic data provides a strong signal of SL. For large-scale multiple hypothesis testing, we develop an extension called ASTER++ that can utilize additional input gene features within the hypothesis testing framework. Our extensive experiments demonstrate the efficacy of ASTER in identifying SL pairs with potential therapeutic benefits.CCS CONCEPTS• Applied computing → Computational genomics; Health informatics; • Mathematics of computing → Hypothesis testing and confidence interval computation.ACM Reference FormatHerty Liany, Anand Jeyasekharan, and Vaibhav Rajan. 2021. ASTER: A Method to Predict Clinically Actionable Synthetic Lethal Genetic Interactions. In Proceedings of ACM Conference. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/nnnnnnn.nnnnnnn