Prognostic and Predictive Immunohistochemistry-Based Biomarkers in Cancer and Immunotherapy

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

Immune checkpoint inhibitors in metastatic melanoma therapy (Review)

An increase in the incidence of melanoma has been observed in recent decades, which poses a significant challenge due to its poor prognosis in the advanced and metastatic stages. Previously, chemotherapy and high doses of interleukin-2 were available treatments for melanoma; however, they offered limited survival benefits and were associated with severe toxicities. The treatment of metastatic melanoma has been transformed by new developments in immunotherapy. Immune checkpoint inhibitors (ICIs), monoclonal antibodies that target cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4), programmed cell death protein 1 (PD-1) and its ligand, PDL-1, have emerged as promising therapeutic options. Commonly used ICIs, such as ipilimumab, nivolumab and pembrolizumab, have been found to be associated with an improved median overall survival, recurrence-free survival and response rates compared to traditional chemotherapies. Combination therapies involving different types of ICIs, such as anti-PD1 with anti-CTLA-4, have further enhanced the overall survival and response rates by targeting various phases of T-cell activation. Additionally, the development of novel biomarkers has facilitated the assessment of responses to ICI therapy, with tissue and serum-based prognostic and predictive biomarkers now available. The increased response observed with ICIs also provides potential for immune-related adverse effects on various organ systems. Further research is required to evaluate the efficacy and safety of various combinations of ICIs, while ongoing clinical trials explore the potential of newer ICIs. Concerns regarding the development of resistance to ICIs also warrant attention. The present review summarizes and discusses the advent of ICIs with a marked significant breakthrough in the treatment of metastatic melanoma, providing improved outcomes compared to traditional therapies.

Signal-On Fluorescence Biosensor for Detection of miRNA-21 Based on ROX labeled Specific Stem-Loop Probe

Background

The abnormal expression of microRNA (miRNA) influences RNA transcription and protein translation, leading to tumor progression and metastasis. Today, reliably identifying aberrant miRNA expression remains challenging, especially when employing quick, simple, and portable detection methods.

Objectives

This study aimed to diagnose and detect the miR-21 biomarker with high sensitivity and specificity.

Methods

Our detection approach involves immobilizing ROX dye-labeled single-stranded DNA probes (ROX-labeled ssDNA) onto MWCNTs to detect target miRNA-21. Initially, adsorbing ROX-labeled ssDNA onto MWCNTs causes fluorescence quenching of ROX. Subsequently, introducing its complementary DNA (cDNA) forms double-stranded DNA (dsDNA), which results in the desorption and release from MWCNTs, thus restoring ROX fluorescence.

Results

The study examined changes in fluorescence intensities before and after hybridization with miRNA-21. The fluorescence emission intensities responded linearly to increases in miR-21 concentration from 10-9 to 3.2 × 10-6 M. The developed fluorescence sensor exhibited a detection limit of 1.12 × 10-9 M.

Conclusions

This work demonstrates that using a nano-biosensor based on carbon nanotubes offers a highly sensitive method for the early detection of colorectal cancer (CRC), supplementing existing techniques.

An integrative analysis of GEO data to identify possible therapeutic biomarkers of prostate cancer and targeting potential protein through Zea mays phytochemicals by virtual screening approaches

Prostate cancer (PC) is a prevalent type of cancer among men. Delaying the treatment of patients with upgraded or upstaged cancer may lead to unmanageable circumstances. The aim of this study is to contribute to the finding of biomarkers that are specific to PC and identify drug candidates derived from plants. The information about cancer is critical for clinicians to make decisions about patient treatment in the era of precision medicine. Advances in genomics technology have opened up new possibilities for identifying genes that are associated with cancer, including PC. This study identifies novel differentially expressed genes for PC. The seven PC microarray datasets were selected from the National Center for Biotechnology Information (NCBI)/Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were found based on a fold change of |logFC| ≥ 1 and an adjusted p-value of <0.05. The DEGs were further studied using several bioinformatics tools, including STRING, CytoHubba, SRplot, Coremine Medical database, FunRich and GeneMANIA, cBioPortal. The six new potential biomarkers, GAGE2A, GAGE12G, GAGE2E, GAGE13, GAGE12F and CSAG1 were identified. These biomarkers are associated with biological processes (BPs) such as cell division, and gene expression regulation, so these genes may have a crucial role in PC progression and may serve as potential biomarkers for PC. A total of 497 phytochemicals from corn plants have been screened against the target protein and found LTS0176591 as the best lead molecule with docking score of -6.31 kcal/mol. Further, molecular mechanics-generalized born surface area (MM-GBSA), molecular dynamics simulation, principal component analysis (PCA), free energy landscape (FEL) and molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) were carried out to validate the findings.Communicated by Ramaswamy H. Sarma.

Clinical Proteomics for Solid Organ Tissues

The evaluation of biopsied solid organ tissue has long relied on visual examination using a microscope. Immunohistochemistry is critical in this process, labeling and detecting cell lineage markers and therapeutic targets. However, while the practice of immunohistochemistry has reshaped diagnostic pathology and facilitated improvements in cancer treatment, it has also been subject to pervasive challenges with respect to standardization and reproducibility. Efforts are ongoing to improve immunohistochemistry, but for some applications, the benefit of such initiatives could be impeded by its reliance on monospecific antibody-protein reagents and limited multiplexing capacity. This perspective surveys the relevant challenges facing traditional immunohistochemistry and describes how mass spectrometry, particularly liquid chromatography-tandem mass spectrometry, could help alleviate problems. In particular, targeted mass spectrometry assays could facilitate measurements of individual proteins or analyte panels, using internal standards for more robust quantification and improved interlaboratory reproducibility. Meanwhile, untargeted mass spectrometry, showcased to date clinically in the form of amyloid typing, is inherently multiplexed, facilitating the detection and crude quantification of 100s to 1000s of proteins in a single analysis. Further, data-independent acquisition has yet to be applied in clinical practice, but offers particular strengths that could appeal to clinical users. Finally, we discuss the guidance that is needed to facilitate broader utilization in clinical environments and achieve standardization.

An update on methods for detection of prognostic and predictive biomarkers in melanoma

The approval of immunotherapy for stage II-IV melanoma has underscored the need for improved immune-based predictive and prognostic biomarkers. For resectable stage II-III patients, adjuvant immunotherapy has proven clinical benefit, yet many patients experience significant adverse events and may not require therapy. In the metastatic setting, single agent immunotherapy cures many patients but, in some cases, more intensive combination therapies against specific molecular targets are required. Therefore, the establishment of additional biomarkers to determine a patient's disease outcome (i.e., prognostic) or response to treatment (i.e., predictive) is of utmost importance. Multiple methods ranging from gene expression profiling of bulk tissue, to spatial transcriptomics of single cells and artificial intelligence-based image analysis have been utilized to better characterize the immune microenvironment in melanoma to provide novel predictive and prognostic biomarkers. In this review, we will highlight the different techniques currently under investigation for the detection of prognostic and predictive immune biomarkers in melanoma.

Recent advancements in tumour microenvironment landscaping for target selection and response prediction in immune checkpoint therapies achieved through spatial protein multiplexing analysis

Immune checkpoint therapies have significantly advanced cancer treatment. Nevertheless, the high costs and potential adverse effects associated with these therapies highlight the need for better predictive biomarkers to identify patients who are most likely to benefit from treatment. Unfortunately, the existing biomarkers are insufficient to identify such patients. New high-dimensional spatial technologies have emerged as a valuable tool for discovering novel biomarkers by analysing multiple protein markers at a single-cell resolution in tissue samples. These technologies provide a more comprehensive map of tissue composition, cell functionality, and interactions between different cell types in the tumour microenvironment. In this review, we provide an overview of how spatial protein-based multiplexing technologies have fuelled biomarker discovery and advanced the field of immunotherapy. In particular, we will focus on how these technologies contributed to (i) characterise the tumour microenvironment, (ii) understand the role of tumour heterogeneity, (iii) study the interplay of the immune microenvironment and tumour progression, (iv) discover biomarkers for immune checkpoint therapies (v) suggest novel therapeutic strategies.

Expression of β-Catenin, E-Cadherin, and α-Smooth Muscle Actin in Basal Cell Carcinoma Before Photodynamic Therapy in Non-recurrent and Recurrent Tumors: Exploring the Ability of Predicting Photodynamic Therapy Outcome

Photodynamic therapy (PDT) is an effective and cosmetically beneficial treatment of low-risk basal cell carcinomas (BCCs). To optimize PDT response, it is important to correctly select tumors. We sought to find markers that could identify such tumors beyond contributions from clinical and histological examination. Studies have shown that β-catenin, E-cadherin, and α-smooth muscle actin (SMA) expression can indicate BCC aggressiveness/BCC invasiveness. We wanted to use these markers in an explorative study to investigate whether they were differently expressed among non-recurring compared with recurring BCCs, to evaluate their ability of predicting PDT outcome. Fifty-two BCCs were stained with antibodies against β-catenin, E-cadherin, and α-SMA, and evaluated using immunoreactive score (IRS), subcellular localization, and stromal protein expression. Results showed that IRS of E-cadherin was significantly different among recurring compared with non-recurring BCCs and with area under a receiver operating characteristic curve of 0.71 (95% confidence interval: 0.56-0.86, p=0.025). Stromal β-catenin expression significantly increased among recurring BCCs. Some recurring BCCs had intense expression in the deep invading tumor edge. In conclusion, E-cadherin, and stromal and deep edge β-catenin expression were most prominent in BCCs that recurred post-PDT, suggesting they could potentially predict PDT outcome. Further studies are needed to investigate whether these results are of clinical value.

Tumors of the Digestive System: Comprehensive Review of Ancillary Testing and Biomarkers in the Era of Precision Medicine

Immunotherapy has remained at the vanguard of promising cancer therapeutic regimens due to its exceptionally high specificity for tumor cells and potential for significantly improved treatment-associated quality of life compared to other therapeutic approaches such as surgery and chemoradiation. This is especially true in the digestive system, where high rates of mutation give rise to a host of targetable tumor-specific antigens. Many patients, however, do not exhibit measurable improvements under immunotherapy due to intrinsic or acquired resistance, making predictive biomarkers necessary to determine which patients will benefit from this line of treatment. Many of these biomarkers are assessed empirically by pathologists according to nuanced scoring criteria and algorithms. This review serves to inform clinicians and pathologists of extant and promising upcoming biomarkers predictive of immunotherapeutic efficacy among digestive system malignancies and the ancillary testing required for interpretation by pathologists according to tumor site of origin.

Conversion surgery for advanced hepatocellular carcinoma after combination treatment of lenvatinib and camrelizumab: a case report

BACKGROUND

Hepatocellular carcinoma (HCC) is an aggressive malignancy with high morbidity and mortality. Conversion therapy can improve surgical resection rate and prolong survival time for patients with advanced HCC. We show that combination therapy with lenvatinib and camrelizumab is a novel approach to downstage unresectable HCC.

CASE PRESENTATION

A 49-year-old man was diagnosed with massive HCC with hilar lymph node and lung metastases. Since radical resection was not feasible, lenvatinib and camrelizumab were administered as first-line therapy. After 10 cycles of camrelizumab and continuous oral administration of lenvatinib, the tumor exhibited striking shrinkage in volume indicating a partial radiological response, accompanied by a reduction in the alpha-fetoprotein levels, followed by salvage resection. Intriguingly, an improvement in predictive biomarkers, like lactate dehydrogenase (LDH) and neutrophil-to-lymphocyte ratio (NLR), was observed. Notably, the pathological examination found high levels of necrosis in the resected tumor, and flow cytometry analysis indicated a significant increase in the ratio of CD5+ and CD5- B lymphocytes in the peripheral blood. After the treatment, the overall survival period was over 24 months, and no recurrence was observed 17-month post-surgery.

CONCLUSIONS

A combination of lenvatinib and camrelizumab may be a new conversion therapy for initially unresectable HCC to resectable HCC, thus contributing to improve the disease prognosis. In addition, the combination regimen could cause an activated immune response, and LDH, NLR, and CD5+ B-cell levels might be predictors for immunotherapy efficacy.

Effect of the preoperative prognostic nutritional index on the long-term prognosis in patients with borderline resectable pancreatic cancer after pancreaticoduodenectomy

Background

The preoperative prognostic nutritional index (PNI) is an indicator of systemic immune-nutritional condition and is a well-known prognostic biomarker in cancer patients. This study aims to reflect the correlation between the preoperative PNI and prognosis in patients with borderline resectable pancreatic cancer (BRPC) after pancreaticoduodenectomy (PD).

Methods

Medical records of patients with BRPC after PD between Jan 2011 and Dec 2021 in our hospital were retrospectively analyzed. The preoperative PNI was calculated, and the receiver operating characteristic curve was obtained based on the preoperative PNI and the 1-year survival rate. Patients were divided into two groups (High-PNI and Low-PNI) following the best cut-off value of the preoperative PNI, and demographic and pathologic findings were compared between the two groups. Univariate and multivariate analysis were performed to identify risk factors in recurrence and long-term survival.

Results

The best cut-off value for the preoperative PNI was 44.6 (sensitivity: 62.46%; specificity: 83.33%; area under the curve: 0.724). Patients in the low-PNI group had significantly shorter recurrence-free survival (P=0.008) and overall survival (P=0.009). The preoperative PNI (P=0.009) and lymph node metastasis (P=0.04) were independent risk factors for tumor recurrence. The preoperative PNI (P=0.001), lymph node metastasis (P=0.04), neoadjuvant chemotherapy (P=0.04) were independent risk factors for long-term survival in patients.

Conclusion

The preoperative PNI, lymph node metastasis, neoadjuvant chemotherapy were independent risk factors for recurrence and long-term survival in patients with BRPC. The preoperative PNI might be an indicator that can predict BRPC patients' recurrence and survival. Patients with high-PNI would benefit from neoadjuvant chemotherapy.

Promoting Best Practice in Cancer Care in Sub Saharan Africa

Promoting best practice in the management of a cancer patient is rooted in the application of new knowledge derived through various sources including population science, laboratory advances, and translational research. Ultimately, the impact of these advances depends on their application at the patient's bedside. A close collaboration between the oncologist and the pathologist is critical in underwriting progress in the management of the cancer patient. Recent advancements have shown that more granular characteristics of the tumor and the microenvironment are defining determinants when it comes to disease course and overall outcome. Whereas, histologic features and basic immunohistochemical characterization were previously adequate to define the tumor and establish treatment recommendation, the growing capability of the pathologist to provide molecular characterization of the tumor and its microenvironment, as well as, the availability of novel therapeutic agents have revolutionized cancer treatment paradigms and improved patient-outcomes and survival. While such capacity and capability appear readily available in most developed high-income countries (HIC), it will take a concerted and collaborative effort of all stakeholders to pave the way in the same stride in the low and middle-income countries (LMIC), which bear a disproportionate burden of human illness and cancers. Patients in the LMIC present with disease at advanced stage and often display characteristics unlike those encountered in the developed world. To keep stride and avoid the disenfranchisement of patients in the LMIC will require greater participation of LMIC patients on the global clinical trial platform, and a more equitable and affordable sharing of diagnostic and therapeutic capabilities between the developed and developing world. Key to the success of this progress and improvement of patient outcomes in the developing world is the close collaboration between the oncologist and the pathologist in this new era of precision and personalized medicine.

Prognosis Value of Immunoregulatory Molecules in Oral Cancer Microenvironment: An Immunohistochemical Study

Objectives: To evaluate the relationship of the immune-checkpoint PD-1/PD-L1 with the clinical evolution of OSCC; to assess survival in OSCC based on the characteristics of TME and histologic risk score; to evaluate the clinical and histopathological relationship of OSCC with immunological TME. Material and Methods: A retrospective study was carried out on 65 samples from patients with OSCC on the floor of the mouth or tongue. Clinicopathological variables and the expression of the biomarkers PD-1, PD-L1, FoxP3, CD4, CD8, CSF1R, and p16 were recorded. The relationship of the clinical and histological variables with the expression of the biomarkers and survival was studied. Results: The univariate and multivariate analysis indicated that positive PD-1 expression was an independent protective factor for survival (overall, disease-free, disease-specific survival) and that high PD-L1 also improved survival. Poorly differentiated histological grades and metastasis were associated with a worse prognosis. Conclusions: PD-1 is a protective survival factor that is maintained independently of PD-L1 expression. High values of PD-L1 expression also improve survival. Higher expression of PD-1 is observed in smaller tumors, and higher expression of PD-L1 is more likely in women. No relationship between the tumor microenvironment and histologic risk score was found to influence the survival patterns studied in the OSCC. There is no evidence of a relationship between the histopathological features and the studied markers, although the positive PD-1 and PD-L1 cases have a lower risk of a high WPOI score, and positive PD-1 expression was associated with a lower DOI.

Proteomics as a Complementary Technique to Characterize Bladder Cancer

Simple Summary

Although immunohistochemistry is a routine technique in clinics, and genomics has been rapidly incorporated, proteomics is a step behind. This general situation is also the norm in bladder cancer research. This review shows the contributions of proteomics to the molecular classification of bladder cancer, and to the study of histopathology due to tissue insults caused by tumors. Furthermore, the importance of proteomics for understanding the cellular and molecular changes as a consequence of the therapy of bladder cancer cannot be neglected.

Abstract

Bladder cancer (BC) is the most common tumor of the urinary tract and is conventionally classified as either non-muscle invasive or muscle invasive. In addition, histological variants exist, as organized by the WHO-2016 classification. However, innovations in next-generation sequencing have led to molecular classifications of BC. These innovations have also allowed for the tracing of major tumorigenic pathways and, therefore, are positioned as strong supporters of precision medicine. In parallel, immunohistochemistry is still the clinical reference to discriminate histological layers and to stage BC. Key contributions have been made to enlarge the panel of protein immunomarkers. Moreover, the analysis of proteins in liquid biopsy has also provided potential markers. Notwithstanding, their clinical adoption is still low, with very few approved tests. In this context, mass spectrometry-based proteomics has remained a step behind; hence, we aimed to develop them in the community. Herein, the authors introduce the epidemiology and the conventional classifications to review the molecular classification of BC, highlighting the contributions of proteomics. Then, the advances in mass spectrometry techniques focusing on maintaining the integrity of the biological structures are presented, a milestone for the emergence of histoproteomics. Within this field, the review then discusses selected proteins for the comprehension of the pathophysiological mechanisms of BC. Finally, because there is still insufficient knowledge, this review considers proteomics as an important source for the development of BC therapies.

Predictive biomarkers for systemic therapy of hepatocellular carcinoma

Introduction: Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the third cancer-related cause of death worldwide. In recent years, several systemic therapy drugs including sorafenib, lenvatinib, regorafenib, cabozantinib, ramucicurab, nivilumab, and pembrolizumab have been approved by FDA for advanced HCC. However, their insufficient efficacy, toxicity, and drug resistance require clinically applicable and validated predictive biomarkers.Areas covered: Our review covers the recent advancements in the identification of proteomic/genomic/epigenomic/transcriptomic biomarkers for predicting HCC treatment efficacy with the use of multi-kinase inhibitors (MKIs), CDK4/6 inhibitors, and immune checkpoint inhibitors (ICIs). Alpha-fetoprotein, des-carboxyprothrombin, vascular endothelial growth factor, angiopoietin-2, and dysregulated MTOR, VEGFR2, c-KIT, RAF1, PDGFRβ have the potential of proteomic/genomic biomarkers for sorafenib treatment. Alanine aminotransferase, aspartate aminotransferase, and albumin-bilirubin grade can predict the efficacy of other MKIs. Rb, p16, and Ki-67, and genes involved in cell cycle regulation, CDK1-4, CCND1, CDKN1A, and CDKN2A have been proposed for CD4/6 inhibitors, while dysregulated TERT, CTNNB1, TP53 FGF19, and TP53 are found to be predictors for ICI efficacy.Expert opinion: There are still limited clinically applicable and validated predictive biomarkers to identify HCC patients who benefit from systemic therapy. Further prospective biomarker validation studies for HCC personalized systemic therapy are required.

Electrochemical biosensors for measurement of colorectal cancer biomarkers

Colorectal cancer (CRC) is associated with one of the highest rates of mortality among cancers worldwide. The early detection and management of CRC is imperative. Biomarkers play an important role in CRC screening tests, CRC treatment, and prognosis and clinical management; thus rapid and sensitive detection of biomarkers is helpful for early detection of CRC. In recent years, electrochemical biosensors for detecting CRC biomarkers have been widely investigated. In this review, different electrochemical detection methods for CRC biomarkers including immunosensors, aptasensors, and genosensors are summarized. Further, representative examples are provided that demonstrate the advantages of electrochemical sensors modified by various nanomaterials. Finally, the limitations and prospects of biomarkers and electrochemical sensors in detection are also discussed. Graphical abstract.

RNA Sequencing-Based Identification of Ganglioside GD2-Positive Cancer Phenotype

The tumor-associated ganglioside GD2 represents an attractive target for cancer immunotherapy. GD2-positive tumors are more responsive to such targeted therapy, and new methods are needed for the screening of GD2 molecular tumor phenotypes. In this work, we built a gene expression-based binary classifier predicting the GD2-positive tumor phenotypes. To this end, we compared RNA sequencing data from human tumor biopsy material from experimental samples and public databases as well as from GD2-positive and GD2-negative cancer cell lines, for expression levels of genes encoding enzymes involved in ganglioside biosynthesis. We identified a 2-gene expression signature combining ganglioside synthase genes ST8SIA1 and B4GALNT1 that serves as a more efficient predictor of GD2-positive phenotype (Matthews Correlation Coefficient (MCC) 0.32, 0.88, and 0.98 in three independent comparisons) compared to the individual ganglioside biosynthesis genes (MCC 0.02-0.32, 0.1-0.75, and 0.04-1 for the same independent comparisons). No individual gene showed a higher MCC score than the expression signature MCC score in two or more comparisons. Our diagnostic approach can hopefully be applied for pan-cancer prediction of GD2 phenotypes using gene expression data.

Biomarkers Predictive of Survival and Response to Immune Checkpoint Inhibitors in Melanoma

Immunotherapy has revolutionized the treatment of melanoma. Targeting of the immune checkpoints cytotoxic T-lymphocyte-associated protein 4 and programmed cell death protein 1 has led to improved survival in a subset of patients. Unfortunately, the use of immune checkpoint inhibitors is associated with significant side effects and many patients do not respond to treatment. Thus, there is an urgent need both for prognostic biomarkers to estimate risk and for predictive biomarkers to determine which patients are likely to respond to therapy. In this review, prognostic and predictive biomarkers that are an active area of research are outlined. Of note, certain transcriptomic signatures are already used in the clinic, albeit not routinely, to prognosticate patients. In the predictive setting, programmed cell death protein ligand 1 expression has been shown to correlate with benefit but is not precise enough to be used as an exclusionary biomarker. Future investigation will need to focus on biomarkers that are easily reproducible, cost effective, and accurate. The use of readily available clinical material, such as serum or hematoxylin and eosin-stained images, may offer one such path forward.

Resistance Mechanism of PD-1/PD-L1 Blockade in the Cancer-Immunity Cycle

In recent years, the PD-1/PD-L1 axis blockade has become a very promising therapy with significant clinical benefits for multiple tumor types. However, some patients still do not respond sufficiently to PD-1/PD-L1 targeted monotherapy. Therefore, investigating the mechanism of PD-1 blockade resistance will assist in exploring new immunotherapy strategies, controlling the progress of the disease, and thus bringing more sustainable survival benefits to patients. The tumor-immune cycle is divided into the following seven steps: the release of cancer antigens, cancer antigen presentation, priming and activation, trafficking of T cells to tumors, infiltration of T cells into tumors, recognition of cancer cells by T cells, and killing of cancer cells. Given that PD-1/PD-L1 blockade is primarily involved in step 7, any abnormalities in the previous steps may affect the efficacy of PD-1/PD-L1 inhibitors and lead to drug resistance. This review discussed the resistance mechanisms of PD-1/PD-L1 blockade in each cancer-immunity step to finding a more suitable treatment population and an optimized combination therapy to exert immunotherapy in tumor treatment to a greater extent.