Many approaches to cancer management are often ineffective due to adverse reactions, drug resistance, or inadequate target specificity of single anti-cancer agents. In contrast, a combinatorial approach with the application of two or more anti-cancer agents at their respective effective dosages can achieve a synergistic effect that boosts cytotoxicity to cancer cells. In cancer, aberrant apoptotic pathways allow cells that should be killed to survive with genetic abnormalities, leading to cancer progression. Mutations in apoptotic mechanism arising during the treatment of cancer through cancer progression can consequently lead to chemoresistance. Natural compound mixtures that are believed to have multiple specific targets with minimal acceptable side-effects are now of interest to many researchers due to their cytotoxic and chemosensitizing activities. Synergistic interactions within a drug mixture enhance the search for potential molecular targets in cancer cells. Nonetheless, biased/flawed scientific evidence from natural products can suggest false positive therapeutic benefits during drug screening. In this review, we have taken these factors into consideration when discussing the evidence for these compounds and their synergistic therapeutic benefits in cancer. While there is limited evidence for clinical efficacy for these mixtures, in vitro data suggest that these preparations merit further investigation, both in vitro and in vivo.

Non-small cell lung cancer (NSCLC) shows variable responses to immunotherapy, highlighting the need for biomarkers to guide patient selection. We applied a spatial multi-omics approach to 234 advanced NSCLC patients treated with programmed death 1-based immunotherapy across three cohorts to identify biomarkers associated with outcome. Spatial proteomics (n = 67) and spatial compartment-based transcriptomics (n = 131) enabled profiling of the tumor immune microenvironment (TIME). Using spatial proteomics, we identified a resistance cell-type signature including proliferating tumor cells, granulocytes, vessels (hazard ratio (HR) = 3.8, P = 0.004) and a response signature, including M1/M2 macrophages and CD4 T cells (HR = 0.4, P = 0.019). We then generated a cell-to-gene resistance signature using spatial transcriptomics, which was predictive of poor outcomes (HR = 5.3, 2.2, 1.7 across Yale, University of Queensland and University of Athens cohorts), while a cell-to-gene response signature predicted favorable outcomes (HR = 0.22, 0.38 and 0.56, respectively). This framework enables robust TIME modeling and identifies biomarkers to support precision immunotherapy in NSCLC.

Identification of candidate anti-cancer molecular mechanisms of compound kushen injection using functional genomics

Purpose: Imaging mass cytometry (IMC) is among the first tools with the capacity for multiplex analysis of more than 40 targets, which provides a novel approach to biomarker discovery. Here, we used IMC to characterize the tumor microenvironment of patients with metastatic melanoma who received immunotherapy in efforts to find indicative factors of treatment response. In spite of the new power of IMC, the image analysis aspects are still limited by the challenges of cell segmentation. Experimental Design: Here, rather than segment, we performed image analysis using a newly designed version of the AQUA software to measure marker intensity in molecularly defined compartments: tumor cells, stroma, T cells, B cells, and macrophages. IMC data were compared with quantitative immunofluorescence (QIF) and digital spatial profiling. Results: Validation of IMC results for immune markers was confirmed by regression with additional multiplexing methods and outcome assessment. Multivariable analyses by each compartment revealed significant associations of 12 markers for progression-free survival and seven markers for overall survival (OS). The most compelling indicative biomarker, beta2-microglobulin (B2M), was confirmed by correlation with OS by QIF in the discovery cohort and validated in an independent published cohort profiled by mRNA expression. Conclusions: Using digital image analysis based on pixel colocalization to assess IMC data allowed us to quantitively measure 25 markers simultaneously on formalin-fixed, paraffin-embedded tissue microarray samples. In addition to showing high concordance with other multiplexing technologies, we identified a series of potentially indicative biomarkers for immunotherapy in metastatic melanoma, including B2M.

In this report we examine candidate pathways perturbed by Compound Kushen Injection (CKI), a Traditional Chinese Medicine (TCM) that we have previously shown to alter the gene expression patterns of multiple pathways and induce apoptosis in cancer cells. We have measured protein levels in Hep G2 and MDA-MB-231 cells for genes in the cell cycle pathway, DNA repair pathway and DNA double strand breaks (DSBs) previously shown to have altered expression by CKI. We have also examined energy metabolism by measuring [ADP]/[ATP] ratio (cell energy charge), lactate production and glucose consumption. Our results demonstrate that CKI can suppress protein levels for cell cycle regulatory proteins and DNA repair while increasing the level of DSBs. We also show that energy metabolism is reduced based on reduced glucose consumption and reduced cellular energy charge. Our results validate these pathways as important targets for CKI. We also examined the effect of the major alkaloid component of CKI, oxymatrine and determined that it had no effect on DSBs, a small effect on the cell cycle and increased the cell energy charge. Our results indicate that CKI likely acts through the effect of multiple compounds on multiple targets where the observed phenotype is the integration of these effects and synergistic interactions.