The Pharmacorank Search Tool for the Retrieval of Prioritized Protein Drug Targets and Drug Repositioning Candidates According to Selected Diseases

We present the Pharmacorank search tool as an objective means to obtain prioritized protein drug targets and their associated medications according to user-selected diseases. This tool could be used to obtain prioritized protein targets for the creation of novel medications or to predict novel indications for medications that already exist. To prioritize the proteins associated with each disease, a gene similarity profiling method based on protein functions is implemented. The priority scores of the proteins are found to correlate well with the likelihoods that the associated medications are clinically relevant in the disease’s treatment. When the protein priority scores are plotted against the percentage of protein targets that are known to bind medications currently indicated to treat the disease, which we termed the pertinency score, a strong correlation was observed. The correlation coefficient was found to be 0.9978 when using a weighted second-order polynomial fit. As the highly predictive fit was made using a broad range of diseases, we were able to identify a general threshold for the pertinency score as a starting point for considering drug repositioning candidates. Several repositioning candidates are described for proteins that have high predicated pertinency scores, and these provide illustrative examples of the applications of the tool. We also describe focused reviews of repositioning candidates for Alzheimer’s disease. Via the tool’s URL, https://protein.som.geisinger.edu/Pharmacorank/, an open online interface is provided for interactive use; and there is a site for programmatic access

Pan‐cancer analysis of TIM‐3 transcriptomic expression reveals high levels in pancreatic cancer and interpatient heterogeneity

Abstract Background T‐cell immunoglobulin and mucin domain‐containing protein 3 (TIM‐3), an immune checkpoint receptor, dampens immune function. TIM‐3 antagonists have entered the clinic. Methods We analyzed TIM‐3 transcriptomic expression in 514 diverse cancers. Transcript abundance was normalized to internal housekeeping genes and ranked (0–100 percentile) to a reference population (735 tumors; 35 histologies [high≥75 percentile rank]). Ninety tumors (17.5%) demonstrated high TIM‐3 expression. Results TIM‐3 expression varied between and within tumor types. However, high TIM‐3 expression was more common in pancreatic cancer (20/55 tumors, 36.4%; odds ratio, 95% confidence interval (pancreatic vs. other tumors) = 3.176 (1.733–5.818; p < 0.001, multivariate]). High TIM‐3 also significantly and independently correlated with high PD‐L1 (p = 0.014) and high CTLA‐4 (p < 0.001) transcriptomic expression (multivariate). Conclusions These observations indicate that TIM‐3 RNA expression is heterogeneous, but more common in pancreatic cancer and in tumors exploiting PD‐L1 and CTLA‐4 checkpoints. Clinical trials with patient selection for matched immune‐targeted combinations may be warranted

LAG‐3 transcriptomic expression patterns across malignancies: Implications for precision immunotherapeutics

Abstract Background Lymphocyte activation gene 3 (LAG‐3) or CD223 is a transmembrane protein that serves as an immune checkpoint which attenuates T‐cell activation. Many clinical trials of LAG‐3 inhibitors have had modest effects, but recent data indicate that the LAG‐3 antibody relatlimab, together with nivolumab (anti‐PD‐1), provided greater benefit than nivolumab alone in patients with melanoma. Methods In this study, the RNA expression levels of 397 genes were assessed in 514 diverse cancers at a clinical‐grade laboratory (OmniSeq: https://www.omniseq.com/). Transcript abundance was normalized to internal housekeeping gene profiles and ranked (0–100 percentile) using a reference population (735 tumors; 35 histologies). Results A total of 116 of 514 tumors (22.6%) had high LAG‐3 transcript expression (≥75 percentile rank). Cancers with the greatest proportion of high LAG‐3 transcripts were neuroendocrine (47% of patients) and uterine (42%); colorectal had among the lowest proportion of high LAG‐3 expression (15% of patients) (all p < 0.05 multivariate); 50% of melanomas were high LAG‐3 expressors. There was significant independent association between high LAG‐3 expression and high expression of other checkpoints, including programmed death‐ligand 1 (PD‐L1), PD‐1, and CTLA‐4, as well as high tumor mutational burden (TMB) ≥10 mutations/megabase, a marker for immunotherapy response (all p < 0.05 multivariate). However, within all tumor types, there was inter‐patient variability in LAG‐3 expression level. Conclusions Prospective studies are therefore needed to determine if high levels of the LAG‐3 checkpoint are responsible for resistance to anti‐PD‐1/PD‐L1 or anti‐CTLA‐4 antibodies. Furthermore, a precision/personalized immunotherapy approach may require interrogating individual tumor immunograms to match patients to the right combination of immunotherapeutic agents for their malignancy

Cancer testis antigen burden (CTAB): a novel biomarker of tumor-associated antigens in lung cancer

Abstract Background Cancer-testis antigens (CTAs) are tumor antigens that are normally expressed in the testes but are aberrantly expressed in several cancers. CTA overexpression drives the metastasis and progression of lung cancer, and is associated with poor prognosis. To improve lung cancer diagnosis, prognostic prediction, and drug discovery, robust CTA identification and quantitation is needed. In this study, we examined and quantified the co-expression of CTAs in lung cancer to derive cancer testis antigen burden (CTAB), a novel biomarker of immunotherapy response. Methods Formalin fixed paraffin embedded (FFPE) tumor samples in discovery cohort (n = 5250) and immunotherapy and combination therapy treated non-small cell lung cancer (NSCLC) retrospective (n = 250) cohorts were tested by comprehensive genomic and immune profiling (CGIP), including tumor mutational burden (TMB) and the mRNA expression of 17 CTAs. PD-L1 expression was evaluated by IHC. CTA expression was summed to derive the CTAB score. The median CTAB score for the discovery cohort of 170 was applied to the retrospective cohort as cutoff for CTAB “high” and “low”. Biomarker and gene expression correlation was measured by Spearman correlation. Kaplan–Meier survival analyses were used to detect overall survival (OS) differences, and objective response rate (ORR) based on RECIST criteria was compared using Fisher’s exact test. Results The CTAs were highly co-expressed (p < 0.05) in the discovery cohort. There was no correlation between CTAB and PD-L1 expression (R = 0.011, p = 0.45) but some correlation with TMB (R = 0.11, p = 9.2 × 10–14). Kaplan–Meier survival analysis of the immunotherapy-treated NSCLC cohort revealed better OS for the pembrolizumab monotherapy treated patients with high CTAB (p = 0.027). The combination group demonstrated improved OS compared to pembrolizumab monotherapy group (p = 0.04). The pembrolizumab monotherapy patients with high CTAB had a greater ORR than the combination therapy group (p = 0.02). Conclusions CTA co-expression can be reliably measured using CGIP in solid tumors. As a biomarker, CTAB appears to be independent from PD-L1 expression, suggesting that CTAB represents aspects of tumor immunogenicity not measured by current standard of care testing. Improved OS and ORR for high CTAB NSCLC patients treated with pembrolizumab monotherapy suggests a unique underlying aspect of immune response to these tumor antigens that needs further investigation

Additional file 1 of Cancer testis antigen burden (CTAB): a novel biomarker of tumor-associated antigens in lung cancer

Additional file 1: Figure S1. Cancer testis antigen (CTA) expression patterns across normal tissue. Normal tissue gene expression data shown was sourced from genotype-tissue expression database (GTEx)

Measurement of the masses and widths of the Σc(2455)+\Sigma_c(2455)^+ and Σc(2520)+\Sigma_c(2520)^+ baryons

International audienceUsing 980  fb-1 of data collected with the Belle detector operating at the KEKB asymmetric-energy e+e- collider, we report the measurements of the masses, and the first measurements of the instrinsic widths, of the Σc(2455)+ and Σc(2520)+ charmed baryons. We find M(Σc(2455)+)-M(Λc+)=166.17±0.05-0.07+0.16  MeV/c2, Γ(Σc(2455)+)=2.3±0.3±0.3  MeV/c2, M(Σc(2520)+)-M(Λc+)=230.9±0.5-0.1+0.5  MeV/c2, and Γ(Σc(2520)+)=17.2-2.1-0.7+2.3+3.1  MeV/c2, where the uncertainties are statistical and systematic, respectively. These measurements can be used to test models of the underlying quark structure of the Σc states

Measurement of the masses and widths of the Σc(2455)+Σ _c ( 2455 )^ + and Σc(2520)+ Σ_c ( 2520 )^+ baryons

Using 980 ${\rm fb}^{-1}$ of data {collected} with the Belle detector operating at the KEKB asymmetric-energy $e^+e^-$ collider, we report the measurements of the masses, and the first measurements of the instrinsic widths, of the $\Sigma_c(2455)^+$ and $\Sigma_c(2520)^+$ charmed baryons. We find $M(\Sigma_c(2455)^+)-M(\Lambda_c^+) = 166.17\pm 0.05^{+0.16}_{-0.07}\ {\rm MeV}/c^2$, $\Gamma(\Sigma_c(2455)^+) = 2.3 \pm 0.3 \pm 0.3\ {\rm MeV/c^2}$, $M(\Sigma_c(2520)^+)-M(\Lambda_c^+) = 230.9 \pm 0.5 ^{+0.5}_{-0.1}\ {\rm MeV}/c^2$, and $\Gamma(\Sigma_c(2520)^+) = 17.2^{+2.3\ +3.1}_{-2.1\ -0.7}\ {\rm MeV}/c^2$, where the uncertainties are statistical and systematic, respectively. These measurements can be used to test models of the underlying quark structure of the $\Sigma_c$ states