3. Tumor-infiltrating lymphocytes and their role in solid tumor progression

Abstract

Tumor-infiltrating lymphocytes (TIL) are an important component of the tumor environment. Their role in tumor growth and progression has been debated for decades. Today, emphasis has shifted to beneficial effects of TIL for the host and to therapies optimizing the benefits by reducing immune suppression in the tumor microenvironment. Evidence indicates that when TIL are present in the tumor as dense aggregates of activated immune cells, tumor prognosis and responses to therapy are favorable. Gene signatures and protein profiling of TIL at the population and single-cell levels provide clues about their phenotype and numbers but also about TIL potential functions in the tumor. Correlations of the TIL data with clinicopathological tumor characteristics, clinical outcome and patients’ survival indicate that TIL exert influence on the disease progression, especially in colorectal carcinomas and breast cancer. At the same time, the recognition that TIL signatures vary with time and cancer progression has initiated investigations of TIL as potential prognostic biomarkers. Multiple mechanisms are utilized by tumors to subvert the host immune system. The balance between pro- and anti-tumor responses of TIL largely depends on the tumor microenvironment, which is unique in each cancer patient. This balance is orchestrated by the tumor, and thus is shifted toward the promotion of tumor growth. Changes occurring in TIL during tumor progression appear to serve as a measure of tumor aggressiveness and potentially provide a key to selecting therapeutic strategies and inform about prognosis.

3.1. Introduction

The immune cells present in the tumor microenvironment belong to both adaptive and innate arms of the immune system and are found in virtually all human solid tumors. They may be present at various densities ranging from subtle infiltration to overt inflammation. As lymphocytes usually constitute the largest component of these immune infiltrates, they are commonly referred to as “Tumor Infiltrating Lymphocytes” or TIL. Attention given to TIL has progressively grown in the last two decades, largely because of the perception that TIL might play a critical role in carcinogenesis and also might be therapeutically useful. In fact, inflammatory infiltrates into tumors have achieved the status of one of the “Hallmarks of Cancer” by Hanahan and Weinberg [1] in recognition of the role they play in tumor progression and in tumor escape from the host immune system. Recent technological advances have allowed for a better examination of tumor infiltrates and for the identification of immune-related gene signatures expressed in the tumor microenvironment (TME). Phenotypic and functional characteristics of TIL, their localization in situ and their interactions with the tumor cells or non-malignant cells residing in the tumor have become a subject of intense investigations worldwide. These studies are aimed at the confirmation and validation of prognostic and predictive significance of TIL in patients with cancer. It has also become clear that cancer cells have a complex relationship with the immune system, and that even subtle differences in immune cell infiltrates into the tumor can result in the eradication of cancer cells or in enhancement of their growth.

The dynamic relationship existing between TIL and the tumor has been extensively evaluated in mouse models of tumor growth [2] as well as human tumor tissues [3]. The TME is formed as a result of prolonged and constantly changing interactions between the developing tumor and the host immune system responsible for immune surveillance [4]. From its inception, the tumor protects itself from elimination by immune cells and gradually develops mechanisms for suppression of their functions. As tumor progresses, TIL accumulating in the TME become dysfunctional and fail to arrest the tumor progression. The mechanisms of tumor-induced immune suppression include a variety of cellular elements, soluble factors and subcellular components and are unique in every tumor [5]. The key role tumor derived factors, including extracellular vesicles (EVs) or exosomes, play in regulating inter-cellular interactions in the TME has emerged as the major theme of cancer research. The results suggest that every tumor creates its own TME and establishes its own ways for disarming the immune system. While the molecular pathways leading to immune suppression in the TME might be the same, the constellation or mix of various suppressive factors seems to be distinct for each tumor. Thus, interactions between the tumor and TIL are unique for each tumor, even for the tumors of the same origin and histology. Further, the heterogeneity in immunoregulatory pathways may exists within the same tumor, depending on regional or local environmental stimuli. The term “tumor heterogeneity” implies that within the tumor mass, there are considerable differences in cellular as well as molecular and genetic characteristics.

In this brief review, I will summarize the current perception of the role TIL play in tumor progression or responses to oncologic therapies and describe immunoregulatory mechanisms that exist in the TME. I will focus on T cells, B cells and natural killer (NK) cells. While other leukocytes, M1 and M2 macrophages, dendritic cells (DC) and neutrophils (PMN) are all important components of the TME, it is TIL that remain in the highlights. This is due to newly acquired insights into potential of TIL as potential prognostic or predictive biomarkers in cancer and also as components of a promising therapeutic strategy, in which in vitro expanded TILs are adoptively transferred to patients with cancer

3.2. Studies of the intra-tumor immune landscape

Technological advances in cellular, molecular and genetic evaluation of TIL populations or single infiltrating immune cells have provided a wealth of novel information about the spatial distribution of TIL in the tumor, frequency of various TIL subsets, and their functional attributes. Given the heterogeneity of human tumors and the complexity of personalized cellular and molecular interactions in the TME, it is not surprising that monitoring of the TME has been a difficult task, and that biomarkers of tumor progression or response to therapy are not readily identifiable. Dissecting the complex interplay between immune and tumor cells to identify such biomarkers requires the integration of multiple currently available approaches into a “systems biology” approach [6]. Systems biology represents a combination of genetic, epigenetic, transcriptional, proteomic and metabolomic methodologies with immunological insights to provide a comprehensive view of the tumor immune landscape [6]. Systems biology. employing multi-omics technologies is most likely to characterize mechanisms underlying cellular interactions in the TME and to define biomarkers of response to therapy [6]. Today, while various multi-omics technologies are slowly being applied to studies of immune-tumor interactions, the integrative analyses of TILs in situ supported by bioinformatics, computational science and clinical correlations are still not widely available and require implementation.

Despite the existing barriers, studies of TIL in situ have rapidly progressed from immunohistology profiling of immune phenotypes or definition of immunoregulatory cell subsets, to highly sophisticated, multi-parameter genetic and immunological analyses of the TME, where interaction of TIL with tumor cells and each other take place. A broad variety of monitoring strategies are now available for studies of TIL and tumor cells in situ [7]. These include sequencing of the whole genome, defining of gene signatures, epigenetic modifications and changes in protein expression of tumor and immune cells. Further, in TIL, we can define the immune score, T- or B-cell receptor repertoires, identify different types of immune cells by flow cytometry or CyTOFF-based mass spectrometry and perform multispectral immunocytochemistry [8–10]. Using these strategies, human tumors can be categorized into immune-cell rich (“hot”) or immune cell-depleted (“cold”) tumors [11]. The former are considered to be immunologically responsive, or “hot,” and the latter immunologically unresponsive (“cold”) tumor types [11]. Thus, the extent of infiltration of immune cells into the TME emerges as a general measure of the tumor response to immunotherapy. “Sterile” or poorly infiltrated tumors might not be suitable candidates for immune therapy.

The mutational tumor load might be a promising predictive measure of therapeutic response, whereby tumors with a high mutational burden, and consequently enriched in neoantigens, are viewed as immunogenic and potentially more responsive when treated with immune therapies [12,13]. Efforts made to correlate mutational tumor loads with immune cell landscapes to reinforce the predictive algorithm of response to therapy are ongoing and remain inconclusive. Whole genome sequencing and RNAseq of FFPE or fresh frozen tumor tissues are routine procedures that are widely used to define the mutational landscape of tumors and to identify the potential driver mutations in individual tumors [14,15,12]. The availability of the TCGA database with its extensive roster of gene profiles for different tumors or types has been a valuable resource for identifying mutations as well as immune subtypes and functional gene modules, including immune-cell specific genes [16]. Next generation sequencing (NGS) in combination with newly developed bioinformatic programs offer the means for establishing gene signatures/patterns not only for tumor cells but also for TIL. The intra-tumoral signatures of these T cells can be determined on a patient-specific basis [17]. Further, NGS data can be applied to the neoantigen prediction pipeline that evaluates antigen-processing, binding to MHC class I and gene expression to generate a map of mutation-associated neoantigens (MANAs) specific to the patient’s HLA haplotype. Neoantigen expression and immune signatures can then be further interrogated by RNAseq.

Single-cell sequencing of tumor cells as well as immune cells is readily applicable to fresh human tumor specimens. Tumor tissues are enzymatically digested and single tumor or single immune cells are isolated by flow cytometry for single cell (sc)RNAseq [18]. This approach provides gene profiles of both tumor and immune cell types and allows for testing of correlations between the mutational tumor landscape and immune cells in the TME. A search for T cells which are naïve, regulatory, cytotoxic or exhausted, based on differentially expressed genes typifying these T cell subsets, identifies distinct clusters of the T cells and allows for heat maps to be constructed and for the estimation of their abundance in the tumor tissue. Special computational algorithms are available to do so, and the immune signatures of TILs can be identified and chartered [19]. Specifically, signatures of immune dysfunction-associated genes, such as, e.g., elevations in the FOXP3 gene expression characterizing Tregs or in genes for exhaustion markers in CD8+ T cells can be established. Overexpression of genes that mediate immune dysfunction in the TME (e.g., TGFβ, CTLA-4, PD-L1) is often a sign of neoplastic progression. Although these analyses performed at the RNA level may be potentially skewed because of the presence of post-transcriptional modifications in proteins that mediate cellular functions, studies of transcriptomes from tumors have been useful in defining the TME in individual tumors (i.e., personalized analysis) or in tumors with a common histologic type.

Protein-based phenotypic and functional analyses of immuno-inhibitory ligands associated with immune dysfunction, such as PD-L1, CTLA4 or TGF-β, are an important tool. Based on results of these analyses, it may be possible to establish an association between the signature of immune dysfunction in the tumor, the immunomodulatory ligands expression in the TME and the genetic alterations identified by NGS. The next critical step would be to link these findings to clinical endpoints, including a patient’s response to therapy and outcome. This type of assessment, which is applicable to FFPE tissue samples and is largely based on genetic profiling of the tumor and of immune cells found in the TME, is slowly eliminating the dependence on conventional pathological examinations. Phenotypic and functional assessments of isolated TILs without mechanistic and genetic insights that shape their physiology have become obsolete. The above-described analyses of TIL in tumor tissues, have resulted in the recognition of TIL as a biomarker of prognosis and response to therapy [17]. Further, TIL and their anti-tumor potential are being explored in adoptive immunotherapy of cancer.

3.3. Immune score in the TME

Favorable associations of dense T-cell infiltrates with improved prognosis of many human cancers have been reported for decades. Immunohistochemistry of fresh-frozen or FFPE tumor sections has been instrumental in establishing the grading scale for immune cell infiltrations into the tumor now referred to as “immune score.” [8]. In 2006, Galon and colleagues demonstrated the prognostic significance of these TILs [20]. The immune score uses systems biology and an objective scoring system to measure the type, density and localization of immune cells within the TME. In a series of studies in colorectal carcinoma [21] and later in other solid tumors [22], Fridman et al performed immunostaining of hundreds of tumor specimens and showed that a strong local immune reaction, including CD3+CD8+ and memory CD45RO+ T cells, correlated with a favorable prognosis regardless of the regional tumor involvement or the tumor stage [22]. In subsequent independent studies, the prognostic role of infiltrating T cells was confirmed and has led to the proposal for routine evaluation of the TME for density, location, phenotype and function of immune cells as a part of the standard pathological examination [23]. The globally-collected data strongly support the predictive value of the immune score [24], which is currently widely employed for testing its predictive value for response to immunotherapies, including immune checkpoint inhibitors (ICIs).

3.4. Anti-tumor effects of TIL

Traditionally, T lymphocytes, and especially CD8+ cytolytic T cells (CTL), have been considered the major anti-tumor immune effector cells. They are MHC class I-restricted and when specific for cognate tumor-associated antigens (TAA) become activated, produce perforin, granzymes and cytokines which induce death of tumor cells but spare non-malignant cells. A subset of CD4+ T helper (Th) cells is essential for providing cytokine-mediated support for CTL expansion and functions. NK cells, which are not MHC restricted and do not require prior sensitization to antigens, can also recognize and eliminate tumor cells by mechanisms that involve a release of perforin, granzymes and cytokines [25]. These lymphocytes are mediators of cellular anti-tumor immunity. B cells, which upon Ag-specific activation give rise to antibody (Ab)-producing plasma cells, mediate humoral anti-tumor immunity. It has been debated whether it is T or B cells that play a more important role in the control of tumor progression. Contributions of NK cells to anti-tumor immunity have been largely considered in the context of antibody-dependent cytotoxicity (ADCC) during cancer therapy with antibodies. Today, it is evident that cooperative interactions of these cells are critical for the development of effective anti-tumor responses. The presence of B cells, which often form follicular-like structures in the TME has been recently recognized as a potential prognostic biomarker, and the involvement of infiltrating NK cells in cooperative anti-tumor effects has been confirmed [26]. These anti-tumor effects of TIL are being actively explored in cancer therapy [26].

3.4.1. CD8+ cytolytic T cells

The presence and effector functions of T cells in the tumor remain the major interest of most studies. Analyses of the diversity in cellular composition of immune infiltrates in various tumor types can define unique tumor “immune signatures” that correlate TIL with outcome, providing prognostically-relevant immune classification of human cancer potentially equal to or better than the conventional tumor-node-metastasis (TNM) classification [27]. In addition to the overall TIL immune score, the presence, frequency and in situ localization of CD8+ T cells in immune tumor infiltrates is of critical importance as is functional evaluation of their anti-tumor activity. The availability of standardized single-cell assays able to detect tumor-antigen-specific T cells (ELISPOT, cytokine flow cytometry and tetramer binding) among TIL, has greatly facilitated evaluations of their potential value as prognostic biomarkers in cancer [28]. However, it has been also observed that tumor epitope-specific CD8+T cells present in situ or in the peripheral circulation of patients with cancer were often preferentially eliminated either directly via the Fas/FasL or the Trail/TrailR pathways [29] or indirectly through the release of tumor-derived exosomes carrying death receptor ligands [30]. The propensity of TIL isolated from human solid tumors to undergo spontaneous apoptosis was measured by Annexin V binding in flow cytometry assays, and tumor-epitope reactive, activated CD8+ T cells which expressed Fas, were shown to be particularly sensitive to tumor-induced effects [29]. Specifically, FasL+ tumor-derived exosomes isolated tumor cell supernatants or plasma of cancer patients have been recently linked to tumor progression, demonstrating that the presence of membrane-tethered FasL, and potentially of other molecules such as PD-L1 or TGF-β in exosomes, could contribute to apoptosis of anti-tumor effector T cells among TIL and thus to tumor escape from the host immune system [31]. In aggregate, these studies suggest that the presence of death–inducing ligands on tumor cells or carried by tumor-derived exosomes contribute to elimination of TIL responsible for anti-tumor effects in the TME [32]. Thus, anti-tumor effector CD8+ T cells accumulating in the TME and expected to eliminate tumor cells become dysfunctional or “exhausted” due to immunosuppressive activities of the tumor. TIL exhaustion in the TME favors tumor progression. For this reason, the “immune score” when used as a biomarker of outcome should contain estimates of tumor-induced suppression, e.g., numbers and disposition of exhausted T cells. These exhausted T cells overexpress various inhibitory surface receptors, such as PD-L1, lymphocyte activation gene-3 (LAG-3), T-cell immunoglobulin and mucin domain-3 (TIM-3); secrete interferon (IFN) γ and low levels of the effector cytokine, tumor necrosis factor (TNF) α. In the TME, where ligands that stimulate signaling via these receptors are commonly present, suppression of anti-tumor responses is profound. These receptors are therapeutic targets for checkpoint inhibition aimed at restoration of anti-tumor activity of T cells [33].

Although activated CD8+ T cells are present in many human tumors, these tumors fail to undergo spontaneous regression. This is likely due to regulatory mechanisms which inhibit T-cell responses in the TME [32]. These mechanisms can operate at the level of tumor cells inducing, e.g., loss of tumor antigens or down-regulation of class I MHC molecules rendering the tumor invisible to CD 8+ effector T cells [31]. Alternatively, as suggested above, T cells up-regulate immune checkpoints or inhibitory pathways that are hard-wired into all T-cell responses to prevent excessive activation and tissue damage. For example, following T-cell receptor (TCR) engagement by an antigen, T cells up-regulate CTLA-4, an inhibitory receptor that counteracts the stimulatory receptor, CD28 [33]. Tumor cells often express PD-L1, a ligand for another inhibitory receptor, PD-1. Activation of the PD-1/PD-L1 pathway in T cells decreases their proliferation, survival and cytokine production [34]. Still another regulatory break is the presence in the tumor microenvironment of suppressor cells, such as Treg (see below) or myeloid-derived suppressor cells. These regulatory cells produce inhibitory cytokines (e.g., IL-10, TGF-β) or suppressive factors which dampen or abrogate anti-tumor immunity [35,36].

Today, in the checkpoint inhibitor era, much attention has been paid to T cell activation/reinvigoration in the periphery and in the TME after immunotherapy. It appears that patients with solid tumors who respond to ICIs have greater CD8+ T cell density at the tumor margin and their numbers/phenotype are associated with the gene inflammation signature and high tumor mutational burden [37]. However, the specificity of CD8+ TIL for tumor-associated antigens or neoantigens remains poorly defined representing a significant challenge for cancer immunologists [37]. NGS of TCR-Vβ repertoire in TILs can reveal different levels of TCR diversity and prevalence in the tumor as compared to peripheral blood, suggesting that antigen-driven proliferation of cognate T cells occurs in the tumor [38]. In some cases, T-cell diversity appears to correlate with the mutational burden of the tumor [39]. Newer data suggest that neoantigen-specific CD8+ T cells are the major effector cells that mediate tumor regression following checkpoint inhibition [37].

A subset of CD8+ T cells present in tumors, and relatively recently identified using transcriptome analysis as tissue resident memory T cells (T_RM), is a heterogenous T cell population with functions of effector and memory T cells [40]. T_RM down-regulate the expression markers that regulate their exit from tissue and overexpress markers for tissue retention. This phenotype enables them to traffic to, reside in and patrol various tissues, exercising a long-term protective role. In tumors, T_RM infiltration was shown to correlate with enhanced patients’ responses to immunotherapy and associates with favorable prognosis. T_RM in the tumor undergo a unique, hybrid effector cell-memory cell differentiation program of effector cells by expression of PD-1, IFN-γ, perforin and granzymes and of memory cells by their stem-like properties [40]. Tumor specific T_RM preferentially reside in the tumor milieu, where they proliferate in response to TAA and combat tumor cells or eliminate transformed cells in situ [40]. The reportedly potent anti-tumor effects of T_RM cells suggest they represent potential therapeutic targets for enhancing responses to immunotherapy.

3.4.2. CD4+ helper T cells

This subset of T cells is present in solid tumors with the frequency that equals or exceeds that of CD8+ T cells. Several subsets of helper T cells (Th) are recognized, including Th1, Th2, Th17 and Treg. The well-known “Th1/Th2” paradigm [41] refers to the balance that exists between the functionally distinct subsets of T helper cells (Th). Th1 cells produce cytokines, notably IL-2 and IFN-γ, which play a role in activating and enhancing expansion as well as effector functions of CD8+ T cells and NK cells [42]. Th1 cells also influence the antigen-presenting capacity of DC, thus shaping CTL responses [43]. In contrast, Th2 cells secrete cytokines that are important for B-cell maturation, clonal expansion and class switching, thus promoting humoral immune responses. The Th1/Th2 ratio is altered in cancer and other diseases, with Th2 cells often outnumbering Th1 cells in the blood and tumor tissues of patients with cancer [44]. There are no surface markers distinguishing these two Th subsets, but cytokine production and gene expression profiles have been used to discriminate Th1 from Th2 responses [45]. In a study of 400 ER-negative breast tumors, the Th1 profile (IL-2, IL-12, IFN-γ) was inversely correlated with the Th2 profile (IL-13, TGF-β), and Th1 responses associated with a lower risk for distant metastases [46]. Th2 responses were associated with a higher risk. The combination of both pathways allowed for a better prediction of metastasis-free survival than either of the pathways alone [46]. This example emphasizes the potential importance of Th1 versus Th2 responses at tumor sites for disease outcome and indicates that immune response developing in the microenvironment of tumors serves as an important prognostic factor.

A relatively recent addition of Th17 cells, characterized by the production of IL-17, to the T-cell repertoire has altered the Th1/Th2 paradigm. The Th17 cells play a major role in autoimmunity, and their involvement in cancer has been less well studied. A study of human breast tumors identified Th17 cells as a prominent component of infiltrates and established a negative association between their presence and the disease stage or number of involved lymph nodes suggesting, that Th17 are involved in anti-tumor responses [47]. In a study of patients with ovarian carcinoma, Kryczek et al reported that patients with higher numbers of Th17 cells had significantly improved overall survival, irrespective of the tumor stage. Further, the frequency of Th17 cells inversely correlated with that of tumor infiltrating FOXP3+ Treg [48]. However, experiments in mouse models of cancer indicate that Th17 may also be involved in pro-tumor functions by promoting angiogenesis [49]. IL-17 has been shown to induce expression of pro-angiogenic factors such as vascular endothelial growth factor, angiotensin, IL-8 and prostaglandin E₂ in stromal, endothelial and tumor cells [49]. The exact cellular mechanisms that determine pro- vs. anti-tumor functions of Th17+ TIL remain unclear and need further investigations. Nevertheless, given that angiogenesis remains a major feature of progressing tumors, the presence and quality of Th17 infiltrates are likely to be of considerable importance in cancer prognosis.

3.4.3. Regulatory T cells (Treg)

This relatively minor subset of CD4+ T cells (~5%) is well represented among TIL, and Treg play a major role in modulating immune responses in situ. Tumors appear to recruit Treg to the tumor microenvironment, where they accumulate, representing a substantial component of TIL in multiple tumor types [reviewed in 33]. The presence and functional competence of Treg inversely correlates with outcome in many, but not all, human tumors [50,36]. The existing conflicting reports in respect to the role of Treg in promoting tumor progression vs. its regression have largely originated from the lack of a definite phenonotypic profile for human Treg. It appears that the CD4+CD25^highFOXP3+ natural (n) Treg, normally responsible for maintaining peripheral tolerance, control cancer-associated inflammation [51], while another subset of Treg, inducible (i) Treg which may or may not be FOXP3+ but produce adenosine and TGF-β, arise by tumor-driven conversion of conventional CD4+ T cells to highly suppressive, therapy-resistant cells. These iTreg appear to be responsible for down-regulating anti-tumor immune responses in situ [51]. The iTreg promote tumor growth, expand and accumulate in cancer and their presence in TIL predicts poor outcome. In ovarian carcinoma, melanoma, breast cancer and glioblastoma, the frequency of Treg among TIL correlated with tumor grade and reduced patient survival [50]. Because Treg are heterogeneous, consisting of many subsets of functionally distinct cells, and because no universal distinguishing marker for human Treg is currently available, their use as a biomarker of prognosis is limited. On the other hand, Treg maintain a strong suppression of effector cells in the TME, and their functional attributes might serve as markers of suppression levels existing in the TME. Treg possess a metabolic profile that is distinct from that of effector T cells [52]. Recent studies showed that glucose uptake by Treg correlates with their poor suppressor function and their long-term instability. In contrast, Treg upregulate lactic acid metabolism, withstand high lactate conditions and successfully proliferate in the TME. These metabolic differences in utilization of the glycolytic pathway by Treg illustrate their flexibility for survival in the hostile TME by excluding glucose uptake in favor of lactic acid [52]. Treg exploit the metabolism in the TME, and unlike effector T cells, thrive in the lactate-rich milieu and mediate high levels of immunosuppression. Additional studies evaluating the role of Treg present in the tumor microenvironment as an independent predictor of prognosis in cancer are necessary.

3.4.4. B cells

B cells originate in the bone marrow and then migrate to secondary lymphoid organs, e.g., lymph nodes, where they interact with antigens, differentiate into plasma cells and produce antigen-specific Abs. TIL populations in human solid tumors include variable proportions of infiltrating B cells. While a search for promising immune correlates of cancer diagnosis, prognosis and survival has been largely limited to T-cell responses, newer reports indicate that B cells might be critically important for outcome. Two recent independent studies provide useful insights into the prognostic role of B cells in cancer. Schmidt and colleagues have reported data that validate the B-cell signature as the most robust prognostic factor in breast cancer and other human tumors [53,54]. These investigators identified the immunoglobulin G kappa chain (IGKC) as an immunologic biomarker of prognosis and response to chemotherapy in hundreds of patients with breast cancer, non-small cell lung cancer (NSCLC) and colorectal cancer (CRC) [54,55]. In this multi-institutional study, the IGKC was microscopically identified as a product of plasma cells present in the tumor stroma and was validated as a prognostic biomarker by the RNA- and protein-based expression studies independently performed in thousands of formalin-fixed, paraffin-embedded specimens at 20 different centers [54]. Expression of the IGKC transcript was the strongest discriminator of patients with breast cancer with and without metastases among the 60 genes found in the B-cell metagene, while transcripts of the T-cell metagene had lesser prognostic significance [53,54]. Infiltrates of both T and B cells were found to be associated with better prognosis. However, the most important finding was that IGKC predicted responses to neoadjuvant therapy in breast cancer and thus qualifies it as the first immune marker of response to cancer treatment. The finding of the B-cell signature as a validated biomarker of prognosis and response to therapy provides a strong support for the role of humoral immunity in controlling cancer [55].

In support of this key role of the B cell signature, Nielsen and colleagues [56] reported that among TIL present in high-grade serous ovarian carcinomas, CD20+ B cells co-localized with activated CD8+ T cells and expressed markers of antigen presentation, including MHC class I and class II antigens, CD40, CD80 and CD86. These B cells were antigen experienced. The presence among TIL of both CD20+ B and CD8+ T cells correlated with a better patient survival than that compared to CD8+ T cells alone. Although these CD20+ B cells had an atypical CD27(−) memory B-cell phenotype, together with CD8+ T cells, they promoted favorable prognosis in ovarian cancer [56].

Recently, the role of tertiary lymphoid structures (TLS), which are ectopic cellular aggregates resembling secondary lymphoid organs in the cellular content and structural organization [57]. TLS are formed in non-lymphoid tissues in response to local inflammation and are found in solid tumors [57]. Composed of the antigen-specific B cells and T cells as well as dendritic cells, TLS drive the anti-tumor immune responses and have an impact on tumor progression. Formation of TLS in the tumor and abundance of TLS associates with favorable clinical outcome [58].

The emerging evidence for a significant role of the B cell signature as a biomarker of prognosis and possibly of metastasis in several human malignancies deserves careful attention particularly in view of novel insights into functional heterogeneity of this lymphocyte subset, which appears to play a pivotal role in regulating T-cell responses [59]. Thus, human B cells were found to express CD39 and CD73, the ectoenzymes hydrolyzing exogenous ATP to adenosine [60]. The ability of activated CD19+ B cells to regulate T cells via the adenosine pathway and adenosine receptor signaling places these lymphoid cells in the category of regulatory elements potentially as effective as Treg [60].

3.4.5. Natural killer (NK) cells

NK cells mediate innate immune responses and can mediate direct cellular cytotoxicity without a need for prior sensitization [26]. NK cells play a key role in cancer immune surveillance. In contrast to T cells, NK cells are not HLA restricted. They are regulated by a set of receptors, such as killer inhibitory receptors or KIRs, and of activating receptors, such as NKG2D and several others [26], which calibrate anti-tumor functions of these cells. As a result, NK cells eliminate tumors that lack MHC class I expression or that overexpress ligands for NKG2D, including MICA, MICB and UL16-binding proteins, which are minimally or not expressed in non-malignant cells or tissues. These ligands are promptly and efficiently induced by stress, including malignant transformation, and their overexpression on activated NK cells is regarded as the “danger signal” marking cells for immune elimination. There is little evidence for an association of the NK- cell presence in the TME and clinical outcome in solid tumors. Nevertheless, there is evidence that NK cells, which express high levels of low-affinity Fc receptors (CD16) for IgG are critical for ADCC. NK cells are also strong IFN-γ producers [61]. Unfortunately, NK cell functions are often found to be down-regulated in cancer, and in a study of highly aggressive NSCLC, NK cells were found to have an altered phenotype and were impaired in the ability to secrete IFN-γ [62]. Tumor- and peripheral blood-derived NK cells in patients with cancer are frequently compromised, and in many cases this impairment has been linked to the tumor progression and poor prognosis [63]. Recently, it has been reported that EVs produced by tumor cells play a key role in regulating of immune surveillance by NK cells, which is dependent on receptor-ligand interactions driven by MICA expression in the tumor-derived EVs [64]. Thus, another mechanism of tumor-induced immune suppression is revealed, and the focus on this mechanism might provide evidence for an association of inhibitory ligand carrying EVs with cancer progression in the near future.

3.5. Summary and conclusions

The anti-tumor immune response, which is mediated by subsets of lymphoid cells, can have a powerful influence on the survival of patients with cancer. In this respect, evidence is especially strong for colorectal and breast cancers, but this is now being extended to other solid tumors [17]. Patients with large infiltrates of T or B cells or increased expression of genes encoding T-cell or B-cell signatures (i.e., high immune score) tend to have better survival compared to those with few tumor-infiltrating immune cells [17]. TIL can be divided into at least three distinct cell types: effector cells, regulatory cells and inflammatory cells, all of which can influence each other’s functions trough production of cytokines, soluble factors and membrane bound EVs. Tumor cells themselves also produce immunosuppressive cytokines, a variety of soluble and masses of EVs decorated with immunoinhibitory ligands, which have direct as well indirect effects on immune cells recruited to the TME [65]. Therefore, cellular composition of the TME and interactions of cells residing within the tumor determine the outcome of anti-tumor immune responses. As neither the cellular composition nor the cytokine milieu in the microenvironment are constant, because they undergo changes as tumors progress from pre-malignant to malignant and eventually metastatic phenotype, the impact TIL may have on outcome is highly variable. Current data suggest that it may be dependent on the balance existing between inflammatory and regulatory TIL. This balance may be a critical part of the underlying molecular mechanisms that are responsible for the influence TIL exert on cancer patient outcome. Understanding of the cellular and molecular mechanisms involved in creating and maintaining this balance is, therefore, necessary for determining of how TIL contribute to survival of patients with cancer and for the selection of therapeutic strategies that could improve patient survival.

List of abbreviations:

ADCC

antibody-dependent cellular cytotoxicity

CTL

cytolytic T cell

CTLA-4

cytotoxic T lymphocyte-associated antigen-4

DC

dendritic cells

EVs

extracellular vesicles

ICIs

immune checkpoint inhibitors

IL

interleukin

IFN-γ

interferon γ

IGKC

IgG kappa chain

MHC

major histocompatibility complex

NK

natural killer cells

NKG2D

nk2G gene

NSCLC

non-small cell lung cancer

PD-1

programmed cell death protein-1

TAA

tumor-associated antigen

TCR

T-cell receptor

TGF-β

transforming growth factor-β

Th

T helper cell

TIL

tumor-infiltrating lymphocytes

TME

tumor microenvironment

Treg

regulatory T cells