Stem Cells in the News (2024)

Screening possible immune functions related to anticancer treatment

Common immune checkpoints were browsed and screened for possible immunotherapeutic value, and the representative immune checkpoint molecules13,14,15 ADORA2A, BTLA, Nectin-2 (CD112), CD160, CD244, PD-L1, CD96, CSF1R, CTLA4, HAVCR2, IDO1, IL10, IL10RB, KDR, KIR2DL1, KIR2DL3, LAG3, LGALS9, PDCD1, PDCD1LG2, PVRL2, TGFB1, TGFBR1, TIGIT, VTCN1, TNF Receptor Superfamily Member 14 (TNFRSF14), TNF superfamily member 4 (TNFSF4), and TNF superfamily member 18 (TNFSF18) were all input into the Tumor and Immune System Interaction Database (TISIDB) for potential effect predication in the integrated repository portal for tumor-immune system interactions16. Primarily, PD-L1, CD112, TNFRSF14, TNFSF4, TNFSF18, CD48, and LGALS9 were selected for their significant differential expression patterns, and the patterns are shown in Fig. S1. The paired red and green colors indicate the expression patterns in multiple organs and systems.

Furthermore, PD-L1 (Fig.1A), CD112 (Fig.1B), TNFRSF14 (Fig.1C), TNFSF4 (Fig.1D), TNFSF18 (Fig.1E), CD48 (Fig.1F), and LGALS9 (Fig.1G) were analyzed for abnormal expression patterns in breast carcinomas. Specifically, CD112, TNFSF4, TNFSF18, and LGALS9 were significantly overexpressed in breast carcinomas, strongly suggesting potent and valuable effects.

Figure 1

Analyzing candidate immune checkpoint molecules targeted by blockade in carcinomas. Carcinomas throughout the body were enrolled for analysis, and multiple systems showed various immune checkpoint molecule patterns. PD-L1 (A), CD112 (B), TNFRSF14 (C), TNFSF4 (D), TNFSF18 (E), CD48 (F), and LGALS9 (G) were analyzed for abnormal expression in breast carcinomas. In each image, the specific quantitative value is shown at the top, and each dot represents the expression in samples. The bar graphs below were used for comparison, and bar height bar represents the median expression of the specific tumor type or normal tissue. Specifically, CD112, TNFSF4, TNFSF18, and LGALS9 were relatively overexpressed in breast carcinomas.

Immunotherapeutic targets participated in multiple breast carcinogenic processes by interacting with key cancer-stimulating factors

The heterogenetic features of breast cancer cause breast carcinomas with different hormone receptor statuses to benefit from different and specific treatment strategies. As a double-edged sword, a specific agent will not function in another kind of breast carcinoma, and to determine the potential of immune checkpoint blockade therapies, native expression signatures and correlations were studied using cBioPortal and Gene Expression Profiling Interactive Analysis 2 (GEPIA2). An expression heat-map was used to visualize the expression patterns of the candidates in red bars, and the selected representative genes described in the first part of Result section are labeled with a red star (Fig.2A). The analysis flowchart is shown in Fig.2B. All the enrolled factors were input and studied for potential functional correlations (Fig. S2). Specifically, the main oncogenes ERBB2, KRAS, and TP53 were analyzed for their intrinsic connections in breast carcinomas, and promising correlations between TNFSF4 and ERBB2, KRAS, and TP53 were confirmed (Fig. S3, Table 1).

Figure 2

Selection of the most representative immune checkpoint molecules targeted by blockade. Expression signatures and correlations were studied using cBioPortal and GEPIA2. (A) Expression heat-map showing the expression of each candidate in a red bar, and the most representative genes are labeled with a red star. The red bars indicate actual data points, and the gray bars indicate that no specific data were available. (B) The analysis flowchart is shown. (C) Nearly all the immunotherapeutic targets showed expanded expression intervals referring to ESR1 and PGR, and TNFSF4, TNFSF18, and CD48 showed increased expression in breast carcinomas without ERBB2, ESR1, and PGR expression. Amplification or mutation of KRAS (D), TP53 (E), or ERBB2 (F) indicated worse predicted survival.

Table 1 The analysis tested in 276 pairs between the 24 tracks in the OncoPrint to reveal the connections among immunotherapies related genes.

In general, nearly all the immunotherapeutic targets showed expanded expression intervals in ESR1+ and PGR+ cases, the existence of which demonstrated a better response to standard (“chemotherapeutic”) and anti-hormone treatments, indicating that immunotherapy may compensate for current deficiencies. More importantly and interestingly, TNFSF4, TNFSF18, and CD48 all showed increased expression in breast carcinomas bearing no ERBB2, ESR1, or PGR expression, strongly suggesting that immunotherapy may show efficacy in all types of breast cancer, and a partially enlarged drawing is shown in Fig.2C. In detail, TNFSF4, TNFSF18 and CD48 showed aberrant expression in breast cancer cases with different genetic backgrounds, including those without KRAS (Fig.2D), TP53 (Fig.2E), or ERBB2 (Fig.2F) expression and activation; these three factors dominated the survival prognosis and led to short predicted survival.

Evaluation of the cluster of TNFSF4, TNFSF18, CD48 and LGALS9 as therapeutic immune therapeutic targets

The clinical significance of a cluster including TNFSF18 (Fig.3A), LGALS9 (Fig.3B), TNFSF4 (Fig.3C) and CD48 (Fig.3D) was also analyzed for the value of these molecules as immunotherapeutic targets, and TNFSF4 and TNFSF18 showed greater significance in predicting disease-free survival and overall survival (OS). KRAS greatly stimulated carcinogenesis and determined the anticancer treatment response. We further explored the correlations of KRAS with TNFSF18 (Fig.3E), LGALS9 (Fig.3F), TNFSF4 (Fig.3G) and CD48 (Fig.3H), and the positive correlation between TNFSF4 and KRAS strongly suggested the prospect of achieving therapeutic effects by using TNFSF4 as a target for manipulation or blockade.

Figure 3

Clinical evaluations of potential therapeutic candidates. Data were acquired from the combined study cohorts of BREAST (METABRIC 2016), BREAST CANCER (MSK 2018), and BREAST INVASIVE CARCINOMA BREAST (TCGA PANCAN 2018). The clinical significance of the cluster including TNFSF18 (A), LGALS9 (B), TNFSF4 (C) and CD48 (D) was analyzed for the value of these molecules as immunotherapeutic targets. The correlations between KRAS and TNFSF18 (E), LGALS9 (F), TNFSF4 (G) or CD48 (H) were analyzed, and the positive correlation between TNFSF4 and KRAS strongly suggested the prospective therapeutic effects of using TNFSF4 as target for manipulation or blockade. (I) A close correlation between TNFSF4 and ALDH1A1 expression was identified. Stem cells with a positive ALDH1A1 phenotype had a shorter survival time (J) and shorter progression-free time (K).

Groups of stem cells are considered the root of cancer recurrence due to their steady status and superior renewal ability. We previously identified stem-like ALDH1A1+ cells in breast cancer groups2,17,18, and in this study, we noticed a close correlation between TNFSF4 and ALDH1A1 expression (Fig.3I), the latter of which indicated shorter survival (Fig.3J) and progression-free times (Fig.3K). These results strongly suggested that oncogenic TNFSF4 may be an effective immunotherapeutic target, and the proposed survival benefits may also be achieved by repressing stem cell expansion, fully assuring a positive outcome for anti-TNFSF4 treatment. The other candidates, CD112, TNFRSF14, and PD-L1, failed to be involved upon further analysis, as indicated by their negative associations with survival (Fig. S4).

Probable mechanism by which TNFSF4 functions

The immune system becomes suppressed as carcinomas become aggressive, and when immune function inhibitors are applied (immune blockade approaches), active immune cells begin to infiltrate and execute cellular functions (Fig.4A). All types of cancer cells, including the heterogenetic subtype cells known as cancer stem cells (CSCs), can be eliminated by immune attack. To investigate the crucial role of the selected immune target, infiltrating lymphocyte functions and connective functional factors were analyzed for insights into the underlying mechanisms. Both ALDH1A1 overexpression (Fig.4B) and TNFSF4 (Fig.4C) overexpression correlated with more active lymphocytes. However, infiltrating immune cells were suppressed by highly expressed immune inhibitors on cells with increased ALDH1A1 (Fig.4D) or TNFSF4 expression (Fig.4E). These results indicated that TNFSF4 can potentially reactivate the immune response and partially function by precisely neutralizing stem cells.

Figure 4

TNFSF4-based immunotherapy may intersect with cancer stem cell signature repression. (A) Schematic figure illustrating the immune response. the immune system becomes suppressed when a carcinoma becomes aggressive. Later, when immune function inhibitors are blocked, active immune cells begin to infiltrate and exert cytotoxic activities against all tumor cells. Spearman correlations between TNFSF4 and immunoinhibitory factors (Y axis) across human cancers (X axis). The items in the column are listed in sequence as follows: ADORA2A, BTLA, CD160, CD244, CD274, CD96, CSF1R, CTLA4, HAVCR2, IDO1, IL10, IL10RB, KDR, KIR2DL1, KIR2DL3, LAG3, LGALS9, PDCD1, PDCD1LG2, PVRL2, TGFB1, TGFBR1, TIGIT, and VTCN1. The infiltrating lymphocyte functions and connective functional factors were analyzed, and both ALDH1A1 overexpression (B) and TNFSF4 overexpression (C) were correlated with more lymphocyte infiltration. Spearman correlations between TNFSF4 and kinds of lymphocytes (Y axis) across human cancers (X axis). The items in the column are listed in sequence as follows: ADORA2A, BTLA, CD160, CD244, CD274, CD96, CSF1R, CTLA4, HAVCR2, IDO1, IL10, IL10RB, KDR, KIR2DL1, KIR2DL3, LAG3, LGALS9, PDCD1, PDCD1LG2, PVRL2, TGFB1, TGFBR1, TIGIT, and VTCN1. However, infiltrating immune cells were suppressed by highly expressed immune inhibitors in cells with increased ALDH1A1 (D) or TNFSF4 expression (E). These results indicated that TNFSF4 blockade treatment could potentially reactivate the immune response and partially function through precisely inhibiting stem cells.

Stem cell signatures predicted the response to immunotherapy

Immunotherapy responses and effects were believed to be correlated with lymphocyte activation and infiltration, and we first assessed the effects of immunotherapies in multiple systems. Treatments targeting TNFSF4 tended to produce relatively good outcomes (Fig.5A). Additionally, TNFSF4-associated TP53 (Fig.5B), KRAS (Fig.5C), and ERBB2 (Fig.5D) all indicated a relatively good immunotherapy response, which further supported the crucial position of TNFSF4. Red-labeled text refers to one specific study, and detailed study information can be reviewed by searching certain PMID numbers in TISIDB.

Figure 5

TNFSF4 blockade therapies could be assessed in the stem cell signature-associated mode. The transcriptomic and genomic profiles of pretreated tumor biopsies from responders and non-responders treated with anti-PDL1 and anti-PD1 antibodies were enrolled for analysis. In total, the responders tended to exhibit higher TNFSF4 expression levels, and each study could be reviewed by searching for a certain PMID number (red labeling). Assessment of real-world immunotherapeutic effects indicated that effects related to TNFSF4 (A) tended to imply better outcomes and that TNFSF4-associated TP53 (B), KRAS (C), and ERBB2 (D) all indicated better immunotherapy response. Increased ALDH1A1 expression indicated shorter disease-specific survival (E) and overall survival (F), and ALDH1A1 surprisingly correlated with higher therapeutic response ratios (G) through clinical data assessment. (H,I) ALDH1A1 was analyzed for its roles in predicting immunotherapy response, and the 5 subgroups C1 (N = 369), C2 (N = 390), C3 (N = 191), C4 (N = 92), and C6 (N = 40) were involved in assessing functional aspects. ALDH1A1 expression dominated in all the subtypes, participating in multiple immune reaction processes. (J,K) Associations between ALDH1A1 expression and molecular subtypes across human cancers were also identified, and the signature of increasing ALDH1A1 expression tended to be found in all kinds of breast carcinomas. Specifically, C1 represents wound healing, C2 represents IFN-gamma dominant, C3 represents inflammatory, C4 represents lymphocyte depleted, C5 represents immunologically quiescent and is not shown, and C6 represents TGF-b dominant.

TNFSF4 and ALDH1A1 were confirmed to participate in immune-activating therapies, and TNFSF4 treatment predicted a therapeutic response. Immunotherapy consistently repressed tumor growth once the immune system was activated, and from the above results, we further found that TNFSF4-associated therapy might also influence stem cell expansion. Increased ALDH1A1 expression indicated shorter disease-specific survival (Fig.5E) and overall survival (Fig.5F), and in clinical assessments, ALDH1A1 surprisingly correlated with higher therapeutic response ratios (Fig.5G), which has not ever been reported or analyzed.

Associations between ALDH1A1 expression and immune subtypes across human cancers were included for analysis, and ALDH1A1 expression dominated in all the subtypes (Fig.5H), participating in multiple immune reaction processes (Fig.5I). Associations between ALDH1A1 expression and molecular subtypes across human cancers were also identified (Fig.5J), and a signature of increasing ALDH1A1 levels tended to be observed in all kinds of breast carcinoma (Fig.5K), indicating the universal therapy-responsive role of ALDH1A1 in achieving better outcomes.

Preliminary exploration of clinical significance

Immunohistochemical (IHC) staining images were acquired from “The Human Protein Atlas” project (funded by the Knut & Alice Wallenberg Foundation), and representative images were arranged referring to different groups in the public dataset (Fig.6A). High expression of TNFSF4 was universally identified in breast carcinoma (Fig.6B) and pointed to poorer survival outcomes (Fig.6C,D). To further verify the potential effects of TNFSF4 on stem cell renewal, we isolated stem cells and identified higher TNFSF4 expression in the CD44+/24− cell group with the luminal A/B phenotype (Fig.6E) and in the ALDH1A1+ cell group with the basal-like phenotype (Fig.6F). For the first time, we derived solid results through database screening and bench-to-clinic exploration; the results strongly suggested the value of TNFSF4-based immunotherapy (Fig.6G,H).

Figure 6

Exploration of the putative clinical roles of TNFSF4. (A) IHC staining images are shown to clarify different expression patterns (left to right, in sequence, < 25%, 25–75%, and > 75%). A lymph node slide was set as a positive control, and an unstained slide was set as a negative control. (B) High RNA expression of TNFSF4 was universally identified in breast carcinoma, with testing and calculation based on FPKM, and the cutoff line is labeled, which was used for clinical predictions. (C,D) Higher TNFSF4 expression pointed to poorer survival outcomes. (E,F) Flow cytometry with FACSAria sorting was applied to isolate stem cells from ZR75-1, MCF-7, and MM-231 cells. (G,H) Stem cells with a CD44+/24− or ALDH1A1+ phenotype were identified and isolated, and the TNFSF4 expression patterns in different cell lines were checked to illustrate the increased expression.