Adaptive Resistance to Cancer Immunotherapy

CD19 (+) B Cell Combined with Prognostic Nutritional Index Predicts the Clinical Outcomes of Patients with Gastric Cancer Who Underwent Surgery

(1) Background: The aim of this study was to explore the predictive ability of lymphocyte subsets for the prognosis of gastric cancer patients who underwent surgery and the prognostic value of CD19 (+) B cell combined with the Prognostic Nutritional Index (PNI). (2) Methods: This study involved 291 patients with gastric cancer who underwent surgery at our institution between January 2016 and December 2017. All patients had complete clinical data and peripheral lymphocyte subsets. Differences in clinical and pathological characteristics were examined using the Chi-square test or independent sample t-tests. The difference in survival was evaluated using Kaplan-Meier survival curves and the Log-rank test. Cox's regression analysis was performed to identify independent prognostic indicators, and nomograms were used to predict survival probabilities. (3) Results: Patients were categorized into three groups based on their CD19 (+) B cell and PNI levels, with 56 cases in group one, 190 cases in group two, and 45 cases in group three. Patients in group one had a shorter progression-free survival (PFS) (HR = 0.444, p < 0.001) and overall survival (OS) (HR = 0.435, p < 0.001). CD19 (+) B cell-PNI had the highest area under the curve (AUC) compared with other indicators, and it was also identified as an independent prognostic factor. Moreover, CD3 (+) T cell, CD3 (+) CD8 (+) T cell, and CD3 (+) CD16 (+) CD56 (+) NK T cell were all negatively correlated with the prognosis, while CD19 (+) B cell was positively associated with the prognosis. The C-index and 95% confidence interval (CI) of nomograms for PFS and OS were 0.772 (0.752-0.833) and 0.773 (0.752-0.835), respectively. (4) Conclusions: Lymphocyte subsets including CD3 (+) T cell, CD3 (+) CD8 (+) T cell, CD3 (+) CD16 (+) CD56 (+) NK T cell, and CD19 (+) B cell were related to the clinical outcomes of patients with gastric cancer who underwent surgery. Additionally, PNI combined with CD19 (+) B cell had higher prognostic value and could be used to identify patients with a high risk of metastasis and recurrence after surgery.

Resistance to immune checkpoint inhibitors in advanced lung cancer: Clinical characteristics, potential prognostic factors and next strategy

Background

Immune checkpoint inhibitors (ICIs) have shown unprecedented clinical benefit in cancer immunotherapy and are rapidly transforming the practice of advanced lung cancer. However, resistance routinely develops in patients treated with ICIs. We conducted this retrospective study to provide an overview on clinical characteristics of ICI resistance, optimal treatment beyond disease progression after prior exposure to immunotherapy, as well as potential prognostic factors of such resistance.

Methods

190 patients diagnosed with unresectable lung cancer who received at least one administration of an anti-programmed cell death 1 (PD-1)/anti-programmed cell death-ligand 1(PD-L1) at any treatment line at Zhongshan Hospital Fudan University between Sep 2017 and December 2019 were enrolled in our study. Overall survival (OS) and progression-free survival (PFS) were analyzed. Levels of plasma cytokines were evaluated for the prognostic value of ICI resistance.

Results

We found that EGFR/ALK/ROS1 mutation and receiving ICI treatment as second-line therapy were risk factors associated with ICI resistance. Patients with bone metastasis at baseline had a significantly shorter PFS1 time when receiving initial ICI treatment. Whether or not patients with oligo-progression received local treatment seemed to have no significant effect on PFS2 time. Systemic therapies including chemotherapy and anti-angiogenic therapy rather than continued immunotherapy beyond ICI resistance had significant effect on PFS2 time. TNF, IL-6 and IL-8 were significantly elevated when ICI resistance. Lower plasma TNF level and higher plasma IL-8 level seemed to be significantly associated with ICI resistance. A nomogram was established to prognosis the clinical outcome of patients treated with ICIs.

Conclusion

Patients with EGFR/ALK/ROS1 mutation, or those receiving ICI treatment as second-line therapy had higher risk of ICI resistance. Patients with bone metastasis had poor prognosis during immunotherapy. For those patients with oligo-progression after ICI resistance, combination with local treatment did not lead to a significantly longer PFS2 time. Chemotherapy and anti-angiogenic therapy rather than continued immunotherapy beyond ICI resistance had significant effect on PFS2 time. Levels of plasma cytokines including TNF, IL-6 and IL-8 were associated with ICI resistance.

Signal pathways and precision therapy of small-cell lung cancer

Small-cell lung cancer (SCLC) encounters up 15% of all lung cancers, and is characterized by a high rate of proliferation, a tendency for early metastasis and generally poor prognosis. Most of the patients present with distant metastatic disease at the time of clinical diagnosis, and only one-third are eligible for potentially curative treatment. Recently, investigations into the genomic make-up of SCLC show extensive chromosomal rearrangements, high mutational burden and loss-of-function mutations of several tumor suppressor genes. Although the clinical development of new treatments for SCLC has been limited in recent years, a better understanding of oncogenic driver alterations has found potential novel targets that might be suitable for therapeutic approaches. Currently, there are six types of potential treatable signaling pathways in SCLC, including signaling pathways targeting the cell cycle and DNA repair, tumor development, cell metabolism, epigenetic regulation, tumor immunity and angiogenesis. At this point, however, there is still a lack of understanding of their role in SCLC tumor biology and the promotion of cancer growth. Importantly optimizing drug targets, improving drug pharmacology, and identifying potential biomarkers are the main focus and further efforts are required to recognize patients who benefit most from novel therapies in development. This review will focus on the current learning on the signaling pathways, the status of immunotherapy, and targeted therapy in SCLC.

Biomarker-driven immunotherapy for precision medicine in prostate cancer

Although immunotherapy has recently revolutionized standard of care in different cancer types, prostate cancer has generally failed to show dramatic responses to immune checkpoint inhibitors. As in other tumors, the goal in prostate cancer is now to target treatments more precisely on patient's individual characteristics through precision medicine. Defects in mismatch repair, mutations in the exonuclease domain of the DNA polymerase epsilon (POLE), high tumor mutational burden and the presence of biallelic loss of CDK12 among others, are predictive biomarkers of response to immunotherapy. In the present review, we summarize the evolving landscape of immunotherapy in prostate cancer, including precision approaches and strategies to define classes of responsive patients and scale up resistance to immune checkpoint inhibitors.

Immune functions as a ligand or a receptor, cancer prognosis potential, clinical implication of VISTA in cancer immunotherapy

Since cancer immunotherapy with immune checkpoint inhibitors of PD/PDL-1 and CTLA-4 limited efficacy to the patients due to resistance during the current decade, novel target is required for customized treatment due to tumor heterogeneity. V-domain Ig-containing suppressor of T cell activation (VISTA), a programmed death protein-1(PD-1) homolog expressed on T cells and on antigen presenting cells(APC), has emerged as a new target in several cancers. Though VISTA inhibitors including CA-170 are considered attractive in cancer immunotherapy to date, the information on VISTA as a potent biomarker of cancer prognosis and its combination therapy is still lacking to date. Thus, in this review, we discussed extracellular domain, ligands, expression, immune functions and clinical implications of VISTA and finally suggested conclusion and perspectives.

A prime/boost vaccine platform efficiently identifies CD27 agonism and depletion of myeloid-derived suppressor cells as therapies that rationally combine with checkpoint blockade in ovarian cancer

Cancer immunotherapies have generated remarkable clinical responses for some patients with advanced/metastatic disease, prompting exploration of rational combination therapies to bolster anti-tumor immunity in patients with limited response or those who experience tumor progression following an initial response to immunotherapy. In contrast to other tumor indications, objective response rates to single-agent PD-1/PD-L1 blockade in ovarian cancer are limited, suggesting a need to identify combinatorial approaches that lead to tumor regression in a setting where checkpoint blockade alone is ineffective. Using a pre-clinical model of aggressive intraperitoneal ovarian cancer, we have previously reported on a heterologous prime/boost cancer vaccine that elicits robust anti-tumor immunity, prolongs survival of tumor-bearing mice, and which is further improved when combined with checkpoint blockade. As tumor control in this model is CD8 + T cell dependent, we reasoned that the prime/boost vaccine platform could be used to explore additional treatment combinations intended to bolster the effects of CD8 + T cells. Using whole tumor transcriptomic data, we identified candidate therapeutic targets anticipated to rationally combine with prime/boost vaccination. In the context of a highly effective cancer vaccine, CD27 agonism or antibody-mediated depletion of granulocytic cells each modestly increased tumor control following vaccination, with anti-PD-1 therapy further improving treatment efficacy. These findings support the use of immunotherapies with well-defined mechanisms(s) of action as a valuable platform for identifying candidate combination approaches for further therapeutic testing in ovarian cancer.

AFP-Inhibiting Fragments for Drug Delivery: The Promise and Challenges of Targeting Therapeutics to Cancers

Alpha fetoprotein (AFP) plays a key role in stimulating the growth, metastasis and drug resistance of hepatocellular carcinoma (HCC). AFP is an important target molecule in the treatment of HCC. The application of AFP-derived peptides, AFP fragments and recombinant AFP (AFP-inhibiting fragments, AIFs) to inhibit the binding of AFP to intracellular proteins or its receptors is the basis of a new strategy for the treatment of HCC and other cancers. In addition, AIFs can be combined with drugs and delivery agents to target treatments to cancer. AIFs conjugated to anticancer drugs not only destroy cancer cells with these drugs but also activate immune cells to kill cancer cells. Furthermore, AIF delivery of drugs relieves immunosuppression and enhances chemotherapy effects. The synergism of immunotherapy and targeted chemotherapy is expected to play an important role in enhancing the treatment effect of patients with cancer. AIF delivery of drugs will be an available strategy for the targeted treatment of cancer in the future.

Single-cell Analysis Technologies for Immuno-oncology Research: from Mechanistic Delineation to Biomarker Discovery

The successes with immune checkpoint blockade (ICB) and chimeric antigen receptor (CAR)-T-cell therapy in treating multiple cancer types have established immunotherapy as a powerful curative option for patients with advanced cancers. Unfortunately, many patients do not derive benefit or long-term responses, highlighting a pressing need to perform complete investigation of the underlying mechanisms and the immunotherapy-induced tumor regression or rejection. In recent years, a large number of single-cell technologies have leveraged advances in characterizing immune system, profiling tumor microenvironment, and identifying cellular heterogeneity, which establish the foundations for lifting the veil on the comprehensive crosstalk between cancer and immune system during immunotherapies. In this review, we introduce the applications of the most widely used single-cell technologies in furthering our understanding of immunotherapies in terms of underlying mechanisms and their association with therapeutic outcomes. We also discuss how single-cell analyses help to deliver new insights into biomarker discovery to predict patient response rate, monitor acquired resistance, and support prophylactic strategy development for toxicity management. Finally, we provide an overview of applying cutting-edge single-cell spatial-omics to point out the heterogeneity of tumor-immune interactions at higher level that can ultimately guide to the rational design of next-generation immunotherapies.

Primary and Acquired Resistance to Immunotherapy in Lung Cancer: Unveiling the Mechanisms Underlying of Immune Checkpoint Blockade Therapy

After several decades without maintained responses or long-term survival of patients with lung cancer, novel therapies have emerged as a hopeful milestone in this research field. The appearance of immunotherapy, especially immune checkpoint inhibitors, has improved both the overall survival and quality of life of patients, many of whom are diagnosed late when classical treatments are ineffective. Despite these unprecedented results, a high percentage of patients do not respond initially to treatment or relapse after a period of response. This is due to resistance mechanisms, which require understanding in order to prevent them and develop strategies to overcome them and increase the number of patients who can benefit from immunotherapy. This review highlights the current knowledge of the mechanisms and their involvement in resistance to immunotherapy in lung cancer, such as aberrations in tumor neoantigen burden, effector T-cell infiltration in the tumor microenvironment (TME), epigenetic modulation, the transcriptional signature, signaling pathways, T-cell exhaustion, and the microbiome. Further research dissecting intratumor and host heterogeneity is necessary to provide answers regarding the immunotherapy response and develop more effective treatments for lung cancer.

Immunotherapy for Ovarian Cancer: Adjuvant, Combination, and Neoadjuvant

Ovarian cancer is the most lethal gynecologic malignancy. Surgery and chemotherapy are the primary treatments for ovarian cancer; however, patients often succumb to recurrence with chemotherapeutic resistance within several years after the initial treatment. In the past two decades, immunotherapy has rapidly developed, and has revolutionized the treatment of various types of cancer. Despite the fact that immunotherapy response rates among ovarian cancer patients remain modest, treatment with immune checkpoint inhibitors (ICIs), chimeric antigen receptor (CAR)- and TCR-engineered T cells is rapidly developing. Therapeutic efficiency could be improved significantly if immunotherapy is included as an adjuvant therapy, in combination with chemotherapy, radiation therapy, and the use of anti-angiogenesis drugs, and poly ADP ribose polymerase inhibitors (PARPi). Newly developed technologies that identify therapeutic targets, predict treatment efficacy, rapidly screen potential immunotherapy drugs, provide neoadjuvant immunotherapy, and utilize nanomedicine technology provide new opportunities for the treatment of ovarian cancer, and have the potential to prolong patient survival. However, important issues that may hinder the efficacy of such approaches, including hyperprogressive disease (HPD), immunotherapy-resistance, and toxicity of the treatments, including neurotoxicity, must be taken into account and addressed for these therapies to be effective.

Sheddable Prodrug Vesicles Combating Adaptive Immune Resistance for Improved Photodynamic Immunotherapy of Cancer

Photodynamic therapy (PDT) capable of eliciting a robust antitumor immune response has been considered an attractive therapeutic approach. However, adaptive immune resistance in PDT underlines the need to develop alternative strategies. The exquisite power of checkpoint blockade can be harnessed to reinvigorate antitumor immune response. Here, we demonstrate that PDT-triggered adaptive immune resistance can be overcome by inactivating indoleamine 2,3-dioxygenase 1 (IDO-1). We rationally designed a tumor-microenvironment-sheddable prodrug vesicle by integrating a PEGylated photosensitizer (PS) and a reduction-sensitive prodrug of IDO-1 inhibitor. The prodrug vesicles were inert during the blood circulation, whereas they specifically accumulated and penetrated at the tumor site through matrix metalloproteinase-2 (MMP-2)-mediated cleavage of the PEG corona to achieve fluorescence-imaging-guided photodynamic therapy (PDT). Compared to PDT alone, the prodrug-vesicle-mediated combination immunotherapy provoked augmented antitumor immunity to eradicate the tumor in both CT26 colorectal and 4T1 breast immunocompetent mouse models. The prodrug vesicles dramatically suppressed tumor reoccurrence, particularly in overexpressing IDO-1 tumor models, i.e., CT26. This study might provide novel insight into the development of new nanomedicine to enhance the efficacy of photodynamic immunotherapy while addressing the adaptive immune resistance.

Emerging Insights Into the Role of the Hippo Pathway in Multiple Myeloma and Associated Bone Disease

Multiple myeloma (MM) is an incurable plasma-cell dyscrasia with numerous treatment options currently available; however, drug resistance is usually inevitable, so there is a constant need for novel treatment approaches. The Hippo pathway has emerged as an important mediator of oncogenesis in solid tumors. More recently, its key role in regulating apoptosis and mediating resistance in MM and other hematologic malignancies has been demonstrated in preclinical studies, which provides a strong basis for further clinical investigation. The Hippo pathway is also implicated in the pathogenesis of MM-induced bone disease, as it regulates both osteoblast and osteoclast function. We provide an overview of the available data regarding the role of the Hippo signaling components in the pathophysiology of MM. A better understanding of the underlying interactions at the molecular and cellular levels will lead to novel and promising treatment approaches.

Optimal control of acute myeloid leukaemia

Acute myeloid leukaemia (AML) is a blood cancer affecting haematopoietic stem cells. AML is routinely treated with chemotherapy, and so it is of great interest to develop optimal chemotherapy treatment strategies. In this work, we incorporate an immune response into a stem cell model of AML, since we find that previous models lacking an immune response are inappropriate for deriving optimal control strategies. Using optimal control theory, we produce continuous controls and bang-bang controls, corresponding to a range of objectives and parameter choices. Through example calculations, we provide a practical approach to applying optimal control using Pontryagin's Maximum Principle. In particular, we describe and explore factors that have a profound influence on numerical convergence. We find that the convergence behaviour is sensitive to the method of control updating, the nature of the control, and to the relative weighting of terms in the objective function. All codes we use to implement optimal control are made available.

Genetics and biology of prostate cancer

Despite the high long-term survival in localized prostate cancer, metastatic prostate cancer remains largely incurable even after intensive multimodal therapy. The lethality of advanced disease is driven by the lack of therapeutic regimens capable of generating durable responses in the setting of extreme tumor heterogeneity on the genetic and cell biological levels. Here, we review available prostate cancer model systems, the prostate cancer genome atlas, cellular and functional heterogeneity in the tumor microenvironment, tumor-intrinsic and tumor-extrinsic mechanisms underlying therapeutic resistance, and technological advances focused on disease detection and management. These advances, along with an improved understanding of the adaptive responses to conventional cancer therapies, anti-androgen therapy, and immunotherapy, are catalyzing development of more effective therapeutic strategies for advanced disease. In particular, knowledge of the heterotypic interactions between and coevolution of cancer and host cells in the tumor microenvironment has illuminated novel therapeutic combinations with a strong potential for more durable therapeutic responses and eventual cures for advanced disease. Improved disease management will also benefit from artificial intelligence-based expert decision support systems for proper standard of care, prognostic determinant biomarkers to minimize overtreatment of localized disease, and new standards of care accelerated by next-generation adaptive clinical trials.