CD8+ T cells play a crucial role in the adaptive immune response against malignancy (80–82). Since activated CD8+ T cells may directly identify and eliminate cancerous and contaminated cells, they are also called cytotoxic T lymphocytes (CTLs) (80, 81). CTLs are the main immune cells that have the ability to regulate tumor growth and mediate responses to cancer immunotherapies. This is accurate despite the fact that certain immune cells, such as macrophages and NK cells, have the ability to cause tumors (81–83). The primary anticancer function of CTL is the production of cytokines such as IFNγ and tumor necrosis factor (TNF), in addition to the exocytosis of cytotoxic granules that include granzymes and perforin (81, 82). CD8+ T cell priming and recruitment in the TME were reported to be dependent on a subgroup of conventional dendritic cells (cDC), known as cDC1 (84). According to the conceptual framework of cancer immunoediting, the tumor can elude the immune onslaught and foster an immunosuppressive TME following a time of early T cell control (80, 85). Conversely, long-term exposure to antigens, as seen in the setting of cancer and chronic viremia, induces T-cell exhaustion. This condition is characterized by a loss of effector capabilities, unique transcriptional patterns, and a persistent expression of inhibitory surface receptors (like PD-1) (86). Consequently, the translation of histological investigations on CD8+ TIL in tumor tissues is complicated by their varied morphologies and functional profiles in the TME (61, 66).

Early analysis indicated that a group of 47 individuals with primary cutaneous melanoma tumors had higher CD8+ TIL levels, which were related to a higher chance of survival. Upon utilizing CD8+ T cell density to stratify the patients, it was observed that the 5-year OS for the low-, moderate-, and high-density cohorts were 25, 44, and 78%, respectively (87). However, in 2011, a larger cohort of more than 180 primary cutaneous melanoma samples revealed no association between patient survival and CD8+ TIL (88). These investigations thus highlight the difficulty in utilizing immunohistochemistry to assess the CD8+ TIL prognostic significance. Numerous studies have looked at the TIL characteristics of metastatic lesions in addition to original tumors. These results show a significant correlation between survival and elevated CD8+ T cell density in Stage III and IV metastatic melanoma tumors (67, 68). As was previously mentioned, CD8+ TIL express a broad range of surface markers and release several functional chemicals (82). Therefore, while investigating the prognostic importance of CD8+ TIL, some research has looked at the utilization of labeling effector molecules or activation markers in addition to identifying CD8. It was demonstrated that TIL positive for the CD8+ T cell effector molecule called Granzyme B (GZMB) was linked to longer O and progression-free survival (PFS) in the Stage II primary melanoma tumors cohort. Additionally, GZMBC TIL were proven to be positive for CD8 by dual IF labeling (48).

Research on the functional condition of T cells in the TME has revealed many biologically significant surface indicators that may help evaluate the prognostic significance of CD8+ TIL in melanoma. Better clinical results in cutaneous melanoma are linked to the presence of the chemokine receptors CCR9 and CXCR3, as well as the c-type lectin NKG2D, on CD8+ TIL. This was corroborated by a flow cytometric analysis of intratumoral CD8+ T cells in metastatic lymph nodes (mLN) (89). The difference between tumor-specific lymphocytes (i.e., those that detect tumor antigens) and bystander TIL is crucial in the TME. In lung and colon cancers, surface-expressed ectonucleotidase CD39 has been shown to be a useful marker for distinguishing tumor-specific CD8+ TIL. This was found by mass cytometry and multiplexed tetramer-based methodology (90). The researchers discovered that T cell immunoreceptors with Ig and ITIM domains (TIGIT), which have been shown to differentiate tumor-specific “exhausted” TIL, and inhibitory receptors like PD-1 are present in bystander TIL (90, 91). The CD8+ TIL diversity in the TME has been shown by sophisticated immunophenotyping technologies. Labeling other markers on CD8+ TIL, such as CD39, TIGIT, or NKG2D, may or may not help predict disease in research and clinical settings, but this is still up for debate. However, when assessing the prognosis of a disease or the potential efficacy of immunotherapy, examination of CD8+ T cells in the TME continues to be one of the most important readouts for intratumoral immune activity (61, 92).

CD4+ T helper (TH) cells are extremely varied and have a phenotype and function similar to CD8+ T cells (93). Moreover, through recently studied pathways, CD4+ T cells are critical for cancer immunity (93, 94). CD4+ T cells have the ability to kill tumor cells directly and cytolytically, as well as create cytokines like IFNγ that strengthen the immune system’s ability to fight cancer (80, 93). Moreover, CD4+ T cells in secondary lymphoid organs can regulate CD8+ CTL and B cell responses. Studies on murine models have demonstrated that CD4+ T cells can boost CD8+ T response efficacy (94). The differentiation of CD4+ T cells into discrete T helper lineages identified by unique transcription factors and cytokine production has also been demonstrated (93, 95). The lineages T follicular helper (TFH), TH1, TH2, TH17, and CD4+FOXP3+ Treg are the most studied of these. It is widely acknowledged that Th1 cells exploit their high IFNγ production to support efficient immune responses against tumors. Consequently, it recruits NK cells and M1 macrophages that have been classically activated in addition to modulating CD8+ TLR activity. Nevertheless, the complex roles that each subgroup plays in various tumor types are still not well understood and need more research (93). Alternatively, Tregs are thought to promote tumorigenesis because of their ability to reduce immunological responses and block effector T cells (96).

As previously indicated, the majority of research on TIL’s prognostic significance in melanoma has used TIL pattern scoring in HandE tissues. Thus, a relatively handful of investigations have looked at TIL subgroups in situ using IHC (61, 66, 79). Using Stage II primary cutaneous melanomas, Van Houdt et al. (48) demonstrated that CD8+ and CD4+ TIL were only associated with improved PFS and not OS, but GZMBC TIL was associated with both prolonged OS and PFS (48). Nevertheless, there are not any solid studies showing the prognostic value of CD4+ TIL evaluation utilizing histopathology in the setting of metastatic melanoma (61, 66). Jacquelot et al. (89) discovered an inverse relationship between the frequencies of CD8+ T cells and the fraction of naïve CD45RA+CD4+ T cells using multi-parameter flow cytometric profiling. This was found in the mLN of patients with stage III cutaneous melanoma. Furthermore, it was observed that patients whose tumors had notably higher percentages of naive CD45RA+CD4+ T cells had significantly shorter PFS. Finally, it was found that CD4+ T cells in metastatic tumors additionally expressed surface markers, PD-1 and CD69. Nevertheless, it is still unclear if evaluating these markers in situ IF or by immunohistochemistry has any predictive value for melanoma (89).

Very little research has used IHC or IF to examine the predictive significance of CD4+ TIL enumeration in melanoma (61, 66). Higher concentrations of CD8+ and CD3+ TIL were successfully linked with OS, but not CD4+ TIL. This was demonstrated by studies that used TMAs created from several anatomic regions of metastatic melanoma samples and IHC to identify the primary TIL subgroups (67). However, in a study that looked only at melanoma metastases inside the SLN and visually counted intratumoral cells, greater CD4+ TIL counts were substantially linked with improved OS and RFS (68). The investigation of distinct TIL subsets within the metastatic SLN can yield valuable insights into the molecular and prognostic aspects of the functions these cells perform in cancer immunity. This is because primary cutaneous melanoma is commonly staged via SLN biopsy (97). The aforementioned data, however, make it more difficult to understand how CD4+ TIL functions in melanoma. Firstly, standardized comparisons across numerous findings are not possible due to the limited number of research looking at melanoma TIL subsets and the variation in methods being utilized to determine and count labeled cells (61, 66). Second, identifying merely the CD4 surface antigen is insufficient to describe CD4+ T helper cell diversity. Although TH1 CD4+ TIL is thought to boost cancer immunity, the functions of TH17 and TH2 are extensively complex. Furthermore, it is unclear how they play a part in the formation and spread of tumors (93, 98). The understanding of how T helper subsets impact tumor formation has primarily come from in vivo mouse models, whereby B16 melanomas have been demonstrated to be eradicated by CD4+ TH1 and TH2 cells (98). However, because T-helper subpopulations are generally defined by the differential expression of important cytokines rather than the expression of distinctive surface markers, investigating them in the context of immunopathology is difficult (93). This has led to several investigations using gene expression profiling to evaluate the presence of TH2 or TH1 hallmark genes in human melanoma samples. According to a report, primary melanoma tumors that spontaneously regress (a clinically confirmed event suggesting host anti-tumor immune response activation) express significantly more TH1-linked genes, such as IL-2 and TNFβ, than tumors that do not. Regressing primary tumors also showed increased gene expression of IFNγ, which is the main TH1 effector cytokine. However, these levels did not become statistically significant (99).

In another investigation, VEGFA production was observed to be greater in CD4+ T cells obtained from the SLN of 13 patients with cutaneous melanoma who had TH2-skewed gene profiles. In this study, both positive and negative SLN were included (100). While the exact mechanism of T cell differentiation into distinct effector subpopulations remains unknown, it is known that specific transcription factors regulate the differentiation of CD4+ T cells into distinct T helper lineages. These include TH1 (T-bet), TH2 (GATA-3), Treg (FOXP3), and TH17 (RORgt), As a result, T-bet+ cell IHC has occasionally been used as a readout for TH1 cells in tumor tissue. Increased levels of T-bet+ cells have been correlated with better patient outcomes in both ovarian and colorectal primary cancers (101, 102). Nevertheless, no comparable research on melanoma has been published in the literature (40, 61, 66). Moreover, studies showing Treg to be T-bet expressing raise doubts regarding the biological validity of using T-bet in dual or single-marker IHC to identify TH1 cells. Levine et al. (103) demonstrated in a seminal study that Treg cells express T-bet consistently in murine models, and that the reduction of T-bet+ Treg in mice led to strong TH1 autoimmune reactions (103). As a result, to evaluate CD4+ TIL in cancer tissues and determine the prognostic and biological significance of each subset, it will be necessary to assess several distinct phenotypic markers in addition to CD4+. This is because earlier studies have cast doubt on previously accepted assertions regarding T helper cell differentiation. This is particularly true given the variety of Treg populations found in cancers and the varying findings from research using FOXP3+ to look at Treg that have penetrated tumors (79, 104).

The innate immune system’s effector cells, known as NK cells, are crucial for eliminating tumor and virus-infected cells (105). Additionally, through their interactions with DCs, they take role in the control of adaptive immune responses (106). A balance of signaling pathways initiated by activating (NKG2D, DNAM-1, NKp30, NKp44, NKp46, etc.) and inhibitory receptors (CD94/NKG2A, members of the killer cell immunoglobulin-like receptor family, etc.) receptors determines the activation state of NK cells. Since they are typically scarce in solid tumors, NK cells are thought to primarily contribute to systemic antitumor defense by preventing the growth of hematogenous metastases. Additionally, reduced functional activity and low activating receptor expression are common characteristics of tumor-infiltrating NK cells (107, 108). The impact of immune-suppressive substances generated by tumor cells or nearby stromal cells, which have been reported in a number of tumor forms, including melanoma, may be the source of this (109, 110). Conversely, in certain tumor forms, a higher number of NK cells was linked to a better prognosis (107, 111). However, it should be mentioned that the majority of research used antibodies against the CD56 or CD57 markers, which are expressed by cell types other than NK cells. In contrast, the use of the NKp46 marker, which is thought to be more NK-specific, has only begun to gain traction afterwards (108, 112). A smaller proportion of CD56^bright NK cells in melanoma patients is associated with a shorter overall and PFS, even though there is no overall difference in the number of circulating NK cells between healthy donors and melanoma patients (113). In stage IV melanoma, the same relationship was seen for NKp46 on circulating NK cells, where more expression was linked to prolonged survival (114). Nevertheless, according to de Coaña et al. (115), there was no relationship between NKp46 expression and OS; instead, low CD69 expression might be a predictor of improved OS (115). Using a different approach, analyzing RNA-seq data from bulk tumor samples, Cursons and colleagues used a NK cell signature to predict NK cell infiltration into melanoma and showed that this correlated with a better survival (116).

B lymphocytes are often seen in relatively small quantities in solid tumors, with a few exceptions. It is unclear how antibody-dependent immunity contributes to the immune response against tumors, and it is still up for debate how the biological activity of tumors is influenced by systemic B-cell response or in situ B-cell accumulation. B lymphocytes have been demonstrated to promote tumor growth or progression in several experimental tumor models (117, 118). However, other research produced the opposite findings (119). According to Nelson (120), the variation in B lymphocytes’ systemic pro- or antitumor effects could be linked to the variety of their functional activities. In addition to secreting various immune suppressive substances and supporting tumor growth through antibodies or immune complexes, B lymphocytes may also serve as efficient antigen-presenting cells that stimulate the anticancer T-cell response (120). T cells make up the majority of melanoma infiltrates, just like in other tumor types, with B-cell frequencies estimated to be between 15% and 20% of all infiltrating lymphocytes (121, 122). The vast majority of B lymphocytes expressing the CD20 marker in studies on 106 primary melanomas were found to be peritumoral, primarily distributed in the stroma surrounding tumor deposits. Additionally, B-cells arranged in dense, follicle-like aggregates were seen in roughly 25% of the samples (123, 124). According to different cancer types and melanoma metastases, these B-cell clusters formed ectopic lymphoid structures with T lymphocytes (125–128). Some of the follicle-like structures showed a network of CD21+ follicular DCs, and in most cases, MECA-79+ HEV-like venules were also seen adjacent to these (124). According to Ladányi et al. (123), there was a correlation between the density of activated (CD25+ or OX40+) T cells and B lymphocytes in the melanoma samples. Additionally, peritumoral densities of B-cells and activated T lymphocytes showed a very bad prognosis in the case of low amounts of both cell types, and intensive B-cell infiltration offered a considerable survival advantage (123). Although there was a trend toward a larger incidence of B-cell aggregates in thicker tumors, their appearance did not correlate with the disease’s outcome (124). The quantity of invading B lymphocytes with a predictive impact was not discovered in a previous investigation with less cases (121).

Currently, the IHC-based identification of many TIL-specific markers is one of the main methods for identifying the lymphocyte infiltrates in the TME (including FOXP3, CD3, and CD8) on successive tumor tissue slices (61, 79). Therefore, measuring lymphocyte densities as ratios like CD4/CD8 or CD8/FOXP3 was studied and has demonstrated prognostic value in other types of tumors. However, it still needs to be validated and thoroughly examined (165, 166). Nevertheless, a brand-new intratumoral lymphocyte scoring system called the “Immunoscore” has emerged as an effective predictive tool in colorectal cancer. According to digitally quantified densities of IHC-labeled CD8+ and CD3+ T cells in the CT and at the IM, immunoscore is a scale that ranges from I0-I4 (164, 167). Using specialist image analysis software (Immunoscore^® Analyzer, HalioDx, France), an operator first recognizes specific locations (tumor, necrosis, healthy tissue, etc.), and then confirms the CD8 and CD3 stains. The software automatically determines an IM that extends 360 mm into the healthy tissue and 360 mm into the malignancy. Immunoscore outperformed the TNM staging system used by the AJCC/IUCC (American Joint Committee on Cancer, International Union for Cancer Control) in stage I, II, and III colorectal cancer. This relates to DFS, OS, and DSS prognostic variables. The primary tumor (T), involvement of the LN (N), and metastases (M) are examined by the TNM staging system (167). Tissue biopsies from more than 2,500 patients with colorectal cancer were examined by Immunoscore in a worldwide multi-center study spanning more than 13 nations. The results showed that the test had excellent repeatability and consistency among various sites. In contrast to patients with a lower Immunoscore, those with an elevated Immunoscore had a considerably lower chance of experiencing a disease recurrence after five years (163).

Attempts were made to apply Immunoscore to other tumor types. These include melanoma, non-small cell lung cancer (NSCLC), and breast cancer, due to its effectiveness in colon cancer. As a result, efforts to clinically validate Immunoscore as a prognostic and predictive marker (for ICI) in various other tumor types are still ongoing. TIL markers including FOXP3 and CD20 have also been added to the Immunoscore evaluation in melanoma (168). Overall, the potential for prognosticating clinical outcomes or ICI predictive efficacy of incorporating new immune markers into a more thorough Immunoscore may be greatly increased, given that Immunoscore has not yet been well investigated for melanoma and several other tumor types (39).

When novel imaging and molecular tools become available, the capacity to examine many signals simultaneously offers enormous promise for the identification of actionable and clinically significant immune markers in cancer. Single-molecule fluorescent in situ hybridization (FISH) has made it possible to evaluate numerous RNA molecules at a single-cell resolution, according to studies. A recent report also showed how to multiplex the profiling of up to 40 proteins at once using an iterative immunofluorescence (4i) based method (169, 170). These technologies are still in the early stages of research; therefore, it is unknown how well they will work for in situ tumor tissue immunophenotyping. Many new image analysis software and detection techniques, such as nucleotide tagging, cyclic immunofluorescence, or metal ion tagging, have been recently developed. This is for the simultaneous detection of numerous protein markers (171). The GeoMx™ digital spatial profiling (DSP) method, which uses antibody probes or RNA attached to photocleavable oligonucleotides, was also recently disclosed by NanoString Technologies. To see tumor (like PanCK) and immunological (like CD45) areas in fluorescent markers-labeled tissue, UV light is channeled toward specific areas of interest using digital micromirror devices. Nevertheless, although this method permits the simultaneous and spatially resolved detection of several protein markers or RNA in FFPE tissue, it is not capable of multiplex viewing of multiple markers on individual cells (172).