The presence of tumor-infiltrating lymphocytes may potentially be a robust predictive and prognostic marker for breast cancer, particularly for triple-negative breast cancer and HER2-positive disease.
Keywords: Breast cancer, Tumor-infiltrating lymphocytes, Adjuvant, Neoadjuvant, Prognosis, Sensitivity analysis
Abstract
Background.
The role of tumor-infiltrating lymphocytes (TILs) in breast cancer (BC) is still an issue for clinical research. Toward this end, a sensitivity analysis of neoadjuvant and adjuvant randomized clinical trials was performed according to disease subtypes.
Methods.
Pathological complete responses (pCRs) after neoadjuvant treatment according to the presence or absence of lymphocyte-predominant BC (LPBC) were extracted and cumulated as odds ratios (ORs) by adopting a random-effects model by subtype. Overall survival hazard ratios as a function of 10% incremental values of stromal TILs (sTILs) in adjuvant trials were extracted. The interaction test was adopted to determine the differential effect according to the subtype.
Results.
Eight trials (5,514 patients) were identified. With regard to neoadjuvant setting (4 studies), a significant interaction (p < .0001) according to LPBC was found. The presence of LPBC was associated with a 29.5% increase in pCR rate compared with non-LPBC (p < .0001). The pCR rate was significantly higher in patients with LPBC in triple-negative BC (TNBC) and HER2-positive BC settings, with an absolute difference of 15.7% (95% confidence interval [CI], 4.9%–26.2%) and 33.3% (95% CI, 23.6%–42.7%), respectively. With respect to the adjuvant setting (4 studies), a significant interaction (p < .0001) according to sTILs was found. A survival benefit was more likely to be determined for HER2-positive BC (p = .025) and TNBC (p < .0001), with no statistically significant difference for estrogen receptor-positive/HER2-negative disease.
Conclusion.
Despite the retrospective nature of this analysis, the presence of TILs may represent a robust predictive and prognostic marker for BC, particularly for TNBC and HER2-positive disease.
Implications for Practice:
This sensitivity analysis of neoadjuvant and adjuvant randomized clinical trials in breast cancer explores the potential predictive and prognostic role of tumor-infiltrating lymphocytes (TILs) according to disease subtypes. The level of TILs present at diagnosis was significantly associated with therapeutic efficacy and prognosis in triple-negative and HER2-positive early breast cancer. This finding may be useful to include in an “immuno-score” in the context of traditional classification of breast cancer to be prospectively considered as a stratification factor in future clinical trials.
Introduction
The complex interaction between the immune system and cancer cells, involving both innate and adaptive immune response, plays a critical role in controlling and eradicating cancer growth and is closely regulated through a delicate balance between inhibiting and activating signals [1–3].
Indeed, the immune system, which is mainly sustained by tumor-infiltrating lymphocytes (TILs), may eliminate tumor cells or allow the tumor to escape immune surveillance (a process known as cancer immunoediting), thus determining tumor progression [4]. Various immunotherapy strategies are being developed to enhance antitumor immune responses, including cytokines, cancer vaccines, adoptive T-cell therapy, and monoclonal antibodies that costimulate immune cells or block immune inhibitory pathways, such as immune checkpoint inhibitors [2, 5–7]. Recently, studies have suggested that checkpoint blockade is a promising strategy for solid and hematologic disease, such as melanoma and non-small cell lung cancer [8–10].
In breast cancer (BC), historically considered a nonimmunosensitive disease, TILs were mainly studied in patients with early-stage disease. Two distinct subsets of lymphocytes were usually assessed: stromal TILs (sTILs; mononuclear cells within the tumor stroma but not in direct contact with invasive carcinoma cells) and intratumoral TILs (iTILs; mononuclear cells that were directly associated with the tumor cells) [11].
The presence of TILs can be observed in all BC subtypes, but the frequency and content of TILs seem to differ across subtypes, with a higher chance of detecting high counts in tumors with high-grade, aggressive, hormone receptor-negative tumors [12]. Furthermore, the presence of TILs can influence the prognosis of BC patients. In this regard, large series of data suggest that tumors with higher TIL counts are associated with good prognosis in contrast with those with lower TILs [13–15]. However, in single studies, the prognostic effect was mostly robust in triple-negative BC (TNBC) and less well-established in other subtypes [16–19].
Besides exploring the value of TILs as a prognostic factor, clinical research is evaluating TILs as a potential predictive factor of pathological complete response (pCR) in the neoadjuvant setting to optimize the overall treatment strategy for early BC. It is well known that the achievement of pCR represents the main prerequisite to improve both disease-free survival and overall survival (OS) [20]. Several studies have shown that higher TIL infiltration in the pretreatment core biopsy specimen is a predictor of response to neoadjuvant chemotherapy [21–23]. Also in this case, TILs seems to predict pCR, especially in TNBC and HER2-positive BC, even if this finding did not constantly emerge in all studies [24].
Nevertheless, most TILs assessments are conducted in retrospective and nonrandomized studies with different methods adopted for the detection and the quantification of the biomarker and different TILs subset assays. Thus, it is not easy to compare the results of studies or speculate about their reliability and the consistency between them. On the basis of this potential bias, the predictive and prognostic role of TILs is still an issue for clinical research.
Clinical efforts to analytically validate and standardize the evaluation of TILs in BC are ongoing. Recently, a series of methodological recommendations for evaluating TILs in BC were released. According to these guidelines, TILs should be reported on hematoxylin and eosin-stained sections for the stromal compartment and primarily scored as a continuous variable. Analysis of TILs as a noncontinuous parameter, such as lymphocyte-predominant BC (LPBC; iTILs and/or sTILs ≥50% or 60%) can also be considered a secondary option. Other TILs assays, such as immunohistochemistry to detect lymphocyte subtypes or molecular techniques, are not recommended for clinical practice [11].
Taking into account these recommendations, we conducted a sensitivity analysis of neoadjuvant and adjuvant randomized clinical trials (RCTs) to explore the potential predictive and prognostic role of TILs according to the disease subtypes.
Methods
The analysis was conducted according to four prespecified steps: (a) definition of the outcomes, (b) definition of the trial selection criteria, (c) definition of the search strategy, and (d) detailed description of the statistical methods used (Data Extraction and Data Synthesis) [25, 26].
Outcome Definition
The analysis was conducted to determine the predictive and prognostic role of TILs in the neoadjuvant and adjuvant setting of early BC according to different disease subtypes. With regard to the neoadjuvant setting, the goal was to evaluate the predictive role of TILs (determined in core biopsy samples obtained before neoadjuvant treatment) in terms of pCR according to BC subtypes. With regard to the adjuvant setting, the objective was to determine the prognostic value of TILs in terms of OS according to BC subtypes.
Trial Identification Criteria
All reports investigating the predictive and prognostic role of TILs in the context of randomized clinical trials published in peer-reviewed journals or presented at the American Society of Clinical Oncology (ASCO), the European Society for Medical Oncology (ESMO), the Federation of European Cancer Societies (now known as the European Cancer Organisation [ECCO]), and the San Antonio Breast Cancer Symposium (SABCS) meetings up to May 31, 2015, were considered.
For the neoadjuvant setting, the articles were screened according to three inclusion criteria, as follows: (a) TILs had to be reported as an LPBC parameter, defined as tumors with at least 60% lymphocyte infiltrate of sTILs or iTILs; (b) TILs had to be measured on hematoxylin and eosin-stained slides; and (c) the relationship between LPBC and pCR rate had to be assessed according to BC subtypes. Publications or presentations not reporting all the criteria were excluded from the analysis to avoid reporting biases and significant heterogeneity between studies.
For the adjuvant setting, the selected articles were screened according to the following inclusion criteria: (a) TILs had to be reported for the stromal compartment and scored as a continuous variable, (b) sTILs had to be measured on hematoxylin and eosin-stained slides; and (c) the relationship between sTILs and OS had to be reported according to different BC subtypes expressed as hazard ratios (HRs) in univariate analysis. All of the criteria had to be met for a publication to be included in this analysis. We excluded TIL assessments in nonrandomized or retrospective studies and performed only by immunohistochemistry or immune gene expression.
Search Strategy
The cutoff for trial publication and/or presentation was May 31, 2015. Updates of RCT were obtained through MEDLINE (PubMed: http://www.ncbi.nlm.nih.gov/PubMed), ASCO (http://www.asco.org), ESMO (http://www.esmo.org), FECS (http://www.ecco-org.eu/), and SABCS (http://www.sabcs.org) website searches. Keywords used for searching were operable or locally advanced BC, tumor-infiltrating lymphocytes (TILs), stromal, adjuvant, neoadjuvant, randomized, overall survival, and pathological complete response. In addition to computer browsing, review and original papers were also scanned in the reference section to look for missing trials. Furthermore, we checked for lectures at major meetings that addressed evaluation of TILs in early-stage BC.
Data Extraction
Data on neoadjuvant and adjuvant outcomes were extracted: The last available update of each trial was considered as the original source. All data were reviewed and separately computed by two investigators (L.C. and E.B.) [26].
Data Synthesis
In the neoadjuvant setting, events for pCR according to the presence or absence of LPBC in different disease subtypes were extracted from papers or presentations. Data were cumulated as odds ratios (ORs) by adopting a random-effects model according to the Der Simonian and Laird method [27], regardless of and according to the subtype. An interaction test (Cochran Q test) was allowed to discriminate if a differential effect according to the subtype did exist [28, 29]. In addition, events rates were determined and 95% confidence intervals (CIs) were derived [27, 30, 31]. In this regard, the sensitivity analysis was performed to test for interaction according to the presence or absence of LPBC.
In the presence of significant interaction (according to both the subtype and the presence or absence of LPBC), the chi-square test was adopted to determine differences between pCR rates. The analysis was conducted in the context of the overall patient sample and according to disease subtype; absolute differences with 95% CIs were thereafter calculated [32].
In the adjuvant setting, HRs with 95% CIs for OS were extracted from papers or presentations. A random-effects model according to the Der Simonian and Laird method was preferred to the fixed-effects model, given the clinical heterogeneity of trials; a heterogeneity test (Cochran Q test) was used as well [28, 29]. Again, the interaction test was determined to weigh treatment effect according to disease subtypes [32].
Calculations were performed by using the licensed Comprehensive Meta-analysis, version 2.0 (Biostat, Englewood, NJ, https://www.meta-analysis.com), and MedCalc, version 14.12.0 (MedCalc Software BVBA, Ostend, Belgium, https://www.medcalc.org/), software.
Results
Selected Trials
Eight trials (5,514 patients) were identified (Fig. 1) [16–18, 21–23, 33, 34]. Of these, 4 RCTs (1,694 patients) [21–23, 33] were conducted in the neoadjuvant setting and 4 RCTs (3,820 patients) [16–18, 34] were conducted in the adjuvant setting. Selected arms of neoadjuvant trials and their characteristics are listed in Table 1. One trial (209 patients) [22] included an arm with luminal disease subtype, 1 trial (442 patients) [21] included an arm with HER2-negative disease, 3 RCTs (625 patients) [21, 23, 33] included an arm with HER2-positve disease, and 2 RCTs (418 patients) [21, 22] included an arm with triple-negative breast cancer. With regard to the pCR definition, pCR was defined in 2 trials as the absence of residual invasive tumor cells in breast and lymph nodes (ypT0/is ypN0) [22, 33] and in 2 trials as the absence of residual invasive or noninvasive tumor cells in breast and nodes (ypT0 ypN0) [21, 23].
Figure 1.
Outline of the search: flow diagram.
Abbreviations: ASCO, American Society of Clinical Oncology; cv, continuous variable; ECCO, European Cancer Organisation; ESMO, European Society for Medical Oncology; LPBC, lymphocyte-predominant breast cancer; OS, overall survival; pCR, pathological complete response; pts, patients; RCTs, randomized clinical trials; SABCS, San Antonio Breast Cancer Symposium; sTILs, stromal tumor-infiltrating lymphocytes.
Table 1.
Characteristics of neoadjuvant randomized trials evaluating tumor-infiltrating lymphocytes, including lymphocyte-predominant breast cancer assay, according to disease subtype
Selected arms of adjuvant trials and their characteristics are listed in Table 2. Three RCTs (2,132 patients) [17, 18, 34] included an arm with luminal disease subtype, 3 RCTs (618 patients) [17, 18, 34] included an arm with HER2-positive disease, and 4 RCTs (1,070 patients) [16–18, 34] included an arm with TNBC.
Table 2.
Characteristics of adjuvant randomized trials evaluating tumor-infiltrating lymphocytes in stromal compartments as continuous variable per 10% increase according to disease subtype
Interaction Analysis
In the neoadjuvant setting, higher pCRs were more likely to be determined in the presence of LPBC (OR, 3.39; 95% CI, 2.24–5.11) in the overall trial sample, regardless of the subtype (Fig. 2A). As shown in Figure 2B, the chance of pCR was higher for LPBC in both HER2-positive BC and TNBC, with ORs of 3.782 (95% CI, 2.23–6.43) and 1.972 (95% CI, 1.29–3.02), respectively. A significant interaction (Q-value = 97.316; p < .0001) according to presence or absence of LPBC in the overall sample was also found considering the pCR event rates (Fig. 2C).
Figure 2.
Neoadjuvant setting. (A): Pathological complete response in the overall population. (B): Pathological complete response according to disease subtypes. (C): Pathological complete response according to lymphocyte-predominant breast cancer LPBC or non-lymphocyte-predominant breast cancer. “Event rate” refers to pathological complete response rate.
Abbreviations: CI, confidence interval; ER, estrogen receptor; LPBC, lymphocyte-predominant breast cancer; OR, odds ratio; pCR, pathological complete response; non-LPBC: non-lymphocyte-predominant breast cancer.
In the adjuvant setting, a significant interaction (Q-value = 17.55; p < .0001) according to sTILs in the overall sample was found, with an OS benefit more likely to be determined in the presence of sTILs treated as a continuous variable for each 10% increment (HR, 1.02; 95% CI, 0.96–1.08).
Sensitivity Analysis
In the neoadjuvant setting, the presence of LPBC was associated with a 29.5% (95% CI, 23.6% to 35.3%) increase in pCR rates compared with non-LPBC (p < .0001; chi-square = 120.59). After taking into account disease subtypes, in HER2-positive BC the pCR rate was significantly higher in patients with LPBC, with an absolute difference of 33.3% (95% CI, 23.6%–42.7%). Similarly, among TNBC patients, the pCR rate was significantly higher in LPBC, with an absolute difference of 15.7% (95% CI, 4.9%–26.2%) (Fig. 3).
Figure 3.
Neoadjuvant setting: sensitivity analysis. Pathological complete response (pCR) rate, with 95% confidence interval in square brackets, in the overall population and according to disease subtypes.
Abbreviations: LPBC, lymphocyte-predominant breast cancer; non-LPBC, non-lymphocyte-predominant breast cancer.
In the adjuvant setting, sTILs treated as a continuous variable (per 10% increments) were significantly associated with a chance of better OS for HER2-positive BC (p = .025) and TNBC (p < .0001); no significant difference was found for estrogen receptor-positive/HER2-negative disease (p = .134) (Fig. 4).
Figure 4.
Adjuvant setting: sensitivity analysis. Overall survival according to disease subtypes.
Abbreviations: CI, confidence interval; ER, estrogen receptor; HR, hazard ratio; OS, overall survival.
Discussion
According to the results reported here, the level of TILs present at diagnosis seems to be significantly associated with therapeutic efficacy and prognosis in early BC in the setting of neoadjuvant and adjuvant treatment, respectively. Indeed, pCR rates were significantly increased by nearly 30% in the presence of TILs reported as LPBC, and the increase of stromal lymphocytes is associated with longer survival after adjuvant treatment. However, both the predictive and prognostic roles of TILs appear to differ according to the histologic subtypes, and they seem to be restricted to TNBC and HER2-positive disease (Figs. 3 and 4).
Triple-negative immunophenotype, which accounts for approximately 15%–20% of all BC, is often characterized by aggressive behavior and worse clinical outcome compared with all the other subtypes [35]. Because TNBCs are not eligible for hormonal therapies or HER2-targeted agents, cytotoxic chemotherapy remains the cornerstone of the current treatment strategies. Therefore, the lack of specific targeted agents and the poor outcome of patients with TNBC indicates that studies are needed to understand the biology of this subtype and to identify predictive biomarkers of response or resistance to specific treatments [36, 37]. In this regard, the concept that TNBC includes a heterogeneous group of diseases with various biological and molecular characteristics determining different clinical outcome is constantly emerging [38].
Generally, TNBC is poorly differentiated and displays a high degree of genomic instability, which may be linked to mutations in DNA repair gene, such as BRCA1 and BRCA2 [39]. These processes may allow to develop a series of neo-mutant peptides, which may become specific tumor neo-antigens, recognized by antigen-presenting cell and presented to the T cells. That may partially explain why TNBCs are more frequently enriched by inflammatory infiltrates compared with hormonal receptor-positive BC [40]. This pathological portrait may mirror the development of a host immune response against the tumor, including adaptive immunity; it may theoretically be implicated in preventing recurrence after surgery in general [4] and therefore explain the prognostic effect in the adjuvant setting.
Moreover, data suggest that chemotherapy may favor the massive release of tumor associated neo-antigens, which follows cytotoxic-induced cell death (called immunogenic cell death) [41]; may suppress regulatory T cells, thus inhibiting the antitumor response; and may restore cytotoxic T cells [42, 43].
As previously reported in other meta-analyses of randomized and nonrandomized trials, our results suggest that TNBC patients with a particularly strong lymphocytic infiltrate (i.e., LPBC) were more likely to experience pCR compared with patients with low lymphocytic infiltrate [19, 24]. In the adjuvant setting, despite the good prognosis of TNBC patients with very high sTILs, these patients should not be spared chemotherapy in light of the recent data derived from two RCTs comparing adjuvant anthracyclines (which induce immunogenic cell death in preclinical models) versus no adjuvant chemotherapy. That study found no interaction between treatment and TILs in the whole study population or in BC subgroups, including TNBC [34]. Therefore, with the current available evidence, TILs should not be used to select patients for withholding chemotherapy.
In addition, the maintenance of tolerance to tumor cells and their evasion from the immune surveillance represent other relevant aspects partly mediated by inhibitory checkpoints, such as cytotoxic T lymphocyte antigen 4 (CTLA-4) and programmed death-1 (PD-1) [2]. Preclinical and clinical data demonstrated that TNBC is associated with higher levels of programmed death-ligand-1 (PD-L1) expression compared with other BC subtypes [44, 45]. In particular, Lehmann et al. identified six different TNBC subtypes (including an immunomodulatory subtype, enriched in immune processes through the overexpression of genes involved in immune signal transduction, cytokine signaling, and immune checkpoints regulators) that could benefit more from checkpoint inhibitors [38]. In the pivotal studies conducted in lung cancer, melanoma, and genitourinary cancers, a differential effect in terms of activity for nivolumab, atezolizumab, and pembrolizumab according to the expression of PD-L1 was consistently present [46]. With regard to the immune-checkpoint inhibition in BC, the results of two immune-checkpoint antibodies, pembrolizumab (anti-PD-1 antibody) and atezolizumab (anti-PD-L1 antibody), in early-phase clinical trials for advanced TNBC were presented at the 2014 San Antonio Breast Cancer Symposium.
The preliminary results of the KEYNOTE-012 trial, a phase Ib study of pembrolizumab in 32 patients with PD-L1-positive metastatic TNBC, showed an overall response rate of 18.5% with long duration of response [47]. Similar results in terms of activity were reported in a phase I trial that evaluated atezolizumab in TNBC with any level of PD-L1 expression; the overall response rate was 19% and the progression-free survival rate at 24 weeks was 27% [48]. The challenge will be to move the clinical evaluation of these drugs in the early setting to test whether they could improve the clinical outcome of TNBC. Pembrolizumab and atezolizumab are not the only checkpoint-blockade agents being evaluated and under investigation in BC. Indeed, other agents, such as ipilimumab and tremelimumab (anti-CTLA-4 antibodies), nivolumab (anti-PD-1 antibody), avelumab and durvalumab (anti-PD-L1 antibodies), are under investigation in advanced and early BC [49].
Unlike in TNBC, the predictive and prognostic roles of TILs in the HER2-positive subtype are less established, particularly in the adjuvant setting. With that treatment, the effect of TILs was not equally consistent in each RCT. Our sensitivity analysis showed a significant prognostic role of TIL in this subtype, with an HR of 0.90 (95% CI, 0.82–0.98; p = .025) for each 10% increase in sTIL (Fig. 4). A limitation in interpreting this results stems from the fact that only the Finland Herceptin (FinHER) trial included the addition of trastuzumab to chemotherapy.
In this regard, the FinHER trial showed a significant association between higher TIL counts and increased trastuzumab benefit in HER2-positive disease in terms of distant disease-free survival [17]. Nevertheless, in the Alliance N9831 trial (excluded from our analysis because of missing OS data), the sTIL increase correlates with benefit of chemotherapy but not with that of chemotherapy plus trastuzumab in terms of relapse-free survival [50]. Thus, although preclinical and clinical evidence highlighted a contribution of immunity to the therapeutic effect of trastuzumab and other monoclonal antibodies, the role of TILs as a predictive marker for anti-HER2 treatment must be further investigated [51].
In the neoadjuvant setting, all the RCTs showed that higher TIL counts correlate to a higher chance of pCR [21, 23, 33]. Recently, Salgado and colleagues demonstrated that higher sTIL counts are associated with higher pCR rates (even if the correlation is nonlinear), as well as better event-free survival, with linear correlation, in HER2-positive patients receiving chemotherapy and anti-HER2 treatment. The authors hypothesized that the anthracycline-based chemotherapy given after surgery could explain the further improvement in long-term outcome. Moreover, in support of the good independent prognostic value of sTILs, the authors showed that patients with high TIL counts in core biopsy specimens at diagnosis had better event-free survival independent of whether they achieved pCR [52]. Thus, as for TNBC, TILs should not be used as a biomarker to withhold chemotherapy. With regard to luminal BC subtypes, the results of this analysis did not show a significant prognostic effect of TILs. To date, no reliable evidence suggests a significant role of TILs in patients with hormonal receptor-positive/HER2-negative BC.
Conclusion
Although this analysis has clear limitations, such as the overall number of included studies and patients, in particular related to luminal BC subtypes, it seems clear that TILs may represent a robust predictive and prognostic marker for TNBC and HER2-postive disease in the context of prospective trials. Several other key questions need to be further investigated. First is the analytic validation and procedural standardization of the method for TILs evaluation and enumeration to ensure consistency. In this regard, given that multiple studies were evaluated for the prognostic and predictive role of TILs, suggesting that the working group provide recommendations for TILs enumeration, prospective evaluation for the standardization of enumeration of TILs in randomized trials going forward is mandatory. The second key question concerns the inclusion of an “immuno-score” in the context of the traditional classification of BC; this should be prospectively considered as a stratification factor in future clinical trials. Third, the definition of the role of the different lymphocytes and the correlation between the immune phenotype and the immune gene profile represent other future issues for research. Finally, as a further research hypothesis, the development of immunotherapeutic approaches (e.g., anti-PD-1 or anti-PD-L1 inhibitors) in combination with chemotherapy could affect the overall TIL count and modulate the immune response. These latest fascinating perspectives may help improve the overall prognosis of BC.
Acknowledgments
This work was supported by a grant from the Italian Association for Cancer Research (AIRC-MFAG 14282, and AIRC-5X1000 12182 and 12214). The funding source had no role in the study design, data collection, data analysis, data interpretation, or writing of the paper.
Author Contributions
Conception/Design: Luisa Carbognin, Sara Pilotto, Rolando Nortilli, Matteo Brunelli, Alessia Nottegar, Emilio Bria
Provision of study material or patients: Luisa Carbognin, Emilio Bria
Collection and/or assembly of data: Luisa Carbognin, Isabella Sperduti, Diana Giannarelli, Emilio Bria, Giampaolo Tortora
Data analysis and interpretation: Luisa Carbognin, Sara Pilotto, Isabella Sperduti, Diana Giannarelli, Emilio Bria
Manuscript writing: Luisa Carbognin, Sara Pilotto, Rolando Nortilli, Matteo Brunelli, Alessia Nottegar, Isabella Sperduti, Diana Giannarelli, Emilio Bria, Giampaolo Tortora
Final approval of manuscript: Luisa Carbognin, Sara Pilotto, Rolando Nortilli, Matteo Brunelli, Alessia Nottegar, Isabella Sperduti, Diana Giannarelli, Emilio Bria, Giampaolo Tortora
Disclosures
Emilio Bria: Celgene, Eli Lilly (CA), Italian Association for Cancer Research (RF), AstraZeneca, Novartis, MSD, Pfizer (H). The other authors indicated no financial relationships.
(C/A) Consulting/advisory relationship; (RF) Research funding; (E) Employment; (ET) Expert testimony; (H) Honoraria received; (OI) Ownership interests; (IP) Intellectual property rights/inventor/patent holder; (SAB) Scientific advisory board
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