Tumor-specific CD8+T cells are exposed to persistent antigenic stimulation which induces a dysfunctional state called “exhaustion.” Though functioning to limit damage caused by immune response, T cell exhaustion leads to attenuated effector function whereby cytotoxic CD8+T cells fail to control tumor progression in the late stage. This pathway is a dynamic process from activation to “progenitor exhaustion” through to “terminally exhaustion” with distinct properties. With the rapid development of immunotherapy via enhancing T cell function, new studies are dissecting the mechanisms and identifying specific biomarkers of dynamic differentiation during the process of exhaustion. Further, although immune checkpoint inhibitors (ICIs) have achieved great success in clinical practice, most patients still show limited efficacy to ICIs. The expansion and differentiation of progenitor exhausted T cells explained the success of ICIs while the depletion of the progenitor T cell pool and the transient effector function of terminally exhausted T cells accounted for the failure of immune monotherapy in the context of exorbitant tumor burden. Thus, combination strategies are urgent to be utilized based on the reduction of tumor burden or the expansion of the progenitor T cell pool. In this review, we aim to introduce the concept of homeostasis of the activated and exhausted status of CD8+T cells in the tumor immune microenvironment, and present recent findings on dynamic differentiation process during T cell exhaustion and the implications for combination strategies in immune therapy.

Claudin 18.2 (CLDN18.2), a tight junction (TJ) family protein controlling molecule exchange between cells, is frequently over-expressed in gastric cancer, pancreatic adenocarcinomas and in a fraction of non–small cell lung cancer cases. The tumor properties indicate that CLDN18.2 could be an attractive drug target for gastric and pancreatic cancers. In this study, we present effective strategies for developing anti-CLDN18.2 therapeutic candidates, based on variable domain of heavy chain of heavy chain antibodies (VHHs). CLDN18.2-specific VHHs were isolated by panning a phage display library from an alpaca immunized with a stable cell line highly expressing CLDN18.2. Humanized VHHs fused with human IgG1 Fc, as potential therapeutic candidates, exhibited desirable binding specificity and affinity to CLDN18.2. In vitro experiments showed that hu7v3-Fc was capable of eliciting both antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC) on CLDN18.2 positive tumor cells. In the mouse xenograft model, the anti-tumor efficacy of hu7v3-Fc was significantly more potent than Zolbetuximab, the benchmark anti-CLDN18.2 monoclonal antibody. Moreover, in vivo biodistribution using zirconium-89 (89Zr) labeled antibodies demonstrated that hu7v3-Fc (89Zr-hu7v3-Fc) exhibited a better tumor penetration and a faster tumor uptake than Zolbetuximab (89Zr-Zolbetuximab), which might be attributed to its smaller size and higher affinity. Taken together, anti-CDLN18.2 hu7v3-Fc is a promising therapeutic agent for human CLDN18.2 positive cancers. Furthermore, hu7v3 has emerged as a potential module for novel CLDN18.2 related therapeutics.

Gene expression profiling holds great potential as a new approach to histological diagnosis and precision medicine of cancers of unknown primary (CUP). Batch effects and different data types greatly decrease the predictive performance of biomarker-based algorithms, and few methods have been widely applied to identify tissue origin of CUP up to now. To address this problem and assist in more precise diagnosis, we have developed a gene expression rank-based majority vote algorithm for tissue origin diagnosis of CUP (TOD-CUP) of most common cancer types. Based on massive tissue-specific RNA-seq data sets (10 553) found in The Cancer Genome Atlas (TCGA), 538 feature genes (biomarkers) were selected based on their gene expression ranks and used to predict tissue types. The top scoring pairs (TSPs) classifier of the tumor type was optimized by the TCGA training samples. To test the prediction accuracy of our TOD-CUP algorithm, we analyzed (1) two microarray data sets (1029 Agilent and 2277 Affymetrix/Illumina chips) and found 91% and 94% prediction accuracy, respectively, (2) RNA-seq data from five cancer types derived from 141 public metastatic cancer tumor samples and achieved 94% accuracy and (3) a total of 25 clinical cancer samples (including 14 metastatic cancer samples) were able to classify 24/25 samples correctly (96.0% accuracy). Taken together, the TOD-CUP algorithm provides a powerful and robust means to accurately identify the tissue origin of 24 cancer types across different data platforms. To make the TOD-CUP algorithm easily accessible for clinical application, we established a Web-based server for tumor tissue origin diagnosis (http://ibi. zju.edu.cn/todcup/).

Background Circulating soluble programmed death ligand 1 (sPD-L1) can negatively regulate T-cell function and serve as a prognostic or predictive marker in a variety of cancers. However, rare studies have evaluated the potential roles of sPD-L1, and no study has estimated its predictive value for the efficacy of immune treatment in colorectal cancer (CRC). Methods Plasma samples from 192 CRC patients were used to estimate correlations between clinicopathological features and sPD-L1, secreted PD-L1 (secPD-L1) and exosomal PD-L1 (exoPD-L1). Baseline and posttreatment sPD-L1 levels were also investigated in 55 patients with metastatic CRC (mCRC) treated with chemotherapy ± targeted therapy and 40 patients with proficient mismatch repair (pMMR) mCRC treated with combination immunotherapy. Both sPD-L1 and secPD-L1 were quantified by enzyme-linked immunosorbent assay, while exoPD-L1 was analyzed using flow cytometry. Results secPD-L1 was the major component and positively correlated with sPD-L1 in CRC, while exoPD-L1 was almost undetectable. Higher levels of sPD-L1 were detected in patients with distant metastasis, especially those with distant lymph node metastasis and tissue combined positive score (CPS) instead of tumor proportion score (TPS). Chemotherapy or targeted therapy did not significantly impact sPD-L1 concentration. Progressive disease on combination immunotherapy was associated with an increase in sPD-L1 level, whereas no significant change was observed in patients with durable clinical benefit. Conclusion sPD-L1 mainly consisted of secPD-L1, and its level was higher in patients with distant metastasis, especially distant lymph node metastasis and positive CPS. sPD-L1 is a potential dynamic marker to identify rapid progression on combination immunotherapy and avoid ineffective treatment for pMMR CRC.