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Abstract

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure Statement
  8. References
  9. Supporting Information

Wilms’ tumor gene 1 (WT1) protein is a promising tumor-associated antigen. In patients with WT1-expressing malignancies, WT1-specific CTLs are spontaneously induced as a result of an immune response to the WT1 protein. In the present study, we performed single cell-level comparative analysis of T cell receptor β-chain variable region (TCR-BV) gene families of a total of 750 spontaneously induced WT1126 peptide (amino acids 126–134, WT1126)-specific CTLs in both HLA-A*0201+ patients with solid tumors and healthy donors (HDs). This is the first report of direct usage analysis of 24 kinds of TCR-BV gene families of WT1126-specific CTLs at the single cell level. Usage analysis with single-cell RT-PCR of TCR-BV gene families of individual FACS-sorted WT1126 tetramer+ CD8+ T cells showed, for the first time, that: (i) BVs 3, 6, 7, 20, 27, and 28 were commonly biased in patients and HDs; (ii) BVs 2, 11, and 15 were biased only in patients; and (iii) BVs 4, 5, 9, and 19 were biased only in HDs. However, statistical analysis of similarity of individual usage frequencies of 24 kinds of TCR-BV gene families between patients and HDs indicated that the usage frequencies of TCR-BV gene families in patients reflected those in HDs. These results should provide us with a novel insight for a better understanding of WT1-specific immune responses. (Cancer Sci 2012; 103: 408–414)

Wilms’ tumor gene (WT1) encodes a zinc-finger transcription factor and plays important roles in the regulation of cell proliferation, differentiation, and apoptosis.(1–3) The WT1 gene was originally isolated as the gene responsible for a childhood renal neoplasm, namely Wilms’ tumor, and was first categorized as a tumor-suppressor gene.(4,5) However, based on the result of a series of studies,(6–8) we proposed that the wild-type WT1 gene had an oncogenic rather than a tumor-suppressor function in various kinds of hematological malignancies and solid tumors. Indeed, the WT1 gene is expressed at high levels in acute myeloid leukemia (AML), acute lymphocytic leukemia, chronic myelogenous leukemia, and myelodysplastic syndromes (MDS), as well as in various types of solid tumors.(9–14) Because a correlation has been shown between WT1 mRNA transcript levels and the amount of minimal residual disease (MRD) in the peripheral blood (PB) or bone marrow of leukemia patients,(15–17) measurement of WT1 mRNA transcripts is now being used to monitor MRD in leukemia patients.

Previous studies have reported that WT1-specific CTLs can be generated from human PBMC in a human leukocyte antigen (HLA) Class I-restricted manner and can lyse WT1-expressing tumor cells as well as WT1 peptide-pulsed target cells.(18,19) Mice immunized with WT1 peptide or WT1 plasmid DNA elicit WT1-specific CTLs and reject challenges by WT1-expressing tumor cells.(20,21) Furthermore, WT1-specific CTLs and antibodies are induced spontaneously in WT1-expressing tumor-bearing patients.(22–24) These results indicate that the WT1 protein is highly immunogenic and a promising target antigen for cancer immunotherapy. In fact, WT1 has been rated as the most promising cancer antigen of 75 tumor-associated antigens.(25)

On the basis of the results of these preclinical studies, clinical studies of WT1 peptide vaccination were undertaken,(26–29) with promising clinical effects, including a reduction in leukemic blast cells and tumor size, as well as long-term stable disease, being seen in association with an increase in the frequency of WT1-specific CD8+ T cells in PB.(26,27) In this context, analysis of the clonality of the WT1-specific CTLs is important to gain a better understanding of the WT1-specific CTL response in WT1-expressing tumor-bearing patients and, further, to obtain clues as to how to enhance WT1-specific CTL responses in WT1 immunotherapy.

Recently, using single-cell RT-PCR analysis of the T cell receptor β-chain variable region (TCR-BV) genes of individual FACS-sorted WT1 tetramer+ CD8+ T cells, we demonstrated biased usage of TCR-BV gene families of WT1235 peptide (amino acids 235–243)-specific CTLs in HLA-A*2402+ patients with AML or MDS, which reflected the biased usage in healthy donors (HDs).(30)

In the present study, we examined usage frequencies of TCR-BV gene families of CTLs specific for WT1126, an HLA-A*0201-restricted CTL epitope, in both patients with solid tumors and HDs and found biased usage for these TCR-BV gene families in both the patients and HDs and that the patterns of biased usage were very similar between the two groups.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure Statement
  8. References
  9. Supporting Information

Samples of PB from patients with solid tumors and HDs.  Analysis of WT1126-specific CTLs in PBMC was approved by the Institutional Review Board for Clinical Research, Osaka University Hospital. After written informed consent had been obtained, PB samples were obtained from six HLA-A*0201+ patients with a solid tumor (patient (PT)-1, -2, -3, -4, -5, and -6) and five HLA-A*0201+ HDs. Expression of WT1 protein in tumor cells was determined by immunohistochemical analysis, as described elsewhere.(31) The PBMC were separated by density gradient centrifugation using Ficoll-Hypaque (Pharmacia, Uppsala, Sweden) and cryopreserved in liquid nitrogen until use. Table 1 summarizes the characteristics of both the patients and HDs.

Table 1.  Characteristics of the patients and healthy donors
 GenderAge (years)DiseaseClinical stagePrior therapy
  1. auto-PBSCT, autologous peripheral blood stem cell transplantation; Chemo, chemotherapy; GBM, glioblastoma multiforme; N/A, not available; Ope, operation; PNET, primitive neuroectodermal tumor; RT, radiation therapy.

Patients
 PT-1M33GBMN/AOpe/RT
 PT-2F56GBMN/AOpe/RT
 PT-3M28GBMN/AOpe/RT/Chemo
 PT-4M18PNETIVOpe/RT/Chemo/auto-PBSCT
 PT-5F53Ovarian cancerIIIcOpe/Chemo
 PT-6F73Cecal cancerIVOpe/Chemo
Healthy donors
 HD-1F23   
 HD-2M45   
 HD-3F24   
 HD-4F25   
 HD-5M37   

Flow cytometric analysis and single-cell sorting of WT1 tetramer+ CD8+ T cells.  Thawed PBMC were rested at 37°C for 1.5 h in RPMI 1640 containing 10% FBS before being stained with phycoerythrin (PE)-labeled HLA-A*0201/WT1126 tetramer (WT1126 tetramer; MBL, Tokyo, Japan) in FACS buffer composed of PBS containing 5% FBS at 37°C for 30 min. The PBMC were then stained with a panel of mAbs at 4°C for 25 min in the dark, washed three times with FACS buffer, and finally resuspended in appropriate quantities of FACS buffer. The following mAbs were used: anti-CD4-FITC, anti-CD16-FITC, anti-CD45RA-allophycocyanin (APC) (BioLegend, San Diego, CA, USA); anti-CD19-FITC, anti-CCR7-PE-Cy7 (BD Pharmingen, San Diego, CA, USA); anti-CD3-peridinin chlorophyII protein (PerCP), anti-CD8-APC-Cy7, anti-CD14-FITC (BD Biosciences, San Jose, CA, USA); and anti-CD56-FITC (eBioscience, San Diego, CA, USA). In the present study, lineage antigen (CD4, CD14, CD16, CD19, and CD56)-negative, CD3-, CD8-, and WT1126 tetramer-positive lymphocytes were defined as WT1126 tetramer+ CD8+ T cells. The WT1126 tetramer+ CD8+ T cells were single-cell sorted using a FACSAria instrument (BD Biosciences), and data were analyzed using FACSDiva software (BD Biosciences).

Synthesis of cDNA from a single cell-sorted WT1126 tetramer+ CD8+ T cell and determination of TCR-BV gene families.  The WT1126 tetramer+ CD8+ T cells were directly single-cell sorted into PCR tubes containing cDNA reaction mix, and cDNA synthesis was performed as described previously.(30) The cDNA was amplified using 24 kinds of TCR-BV gene family-specific forward primers and a constant region-specific reverse primer.(30) Next, the PCR products were amplified by semi-nested PCR for the screening of the BV gene family as follows: the first PCR product was put into eight separate tubes, each of which was filled with a reaction mix containing the reagents, one of eight kinds of screening sets of BV gene family-specific forward primers and the reverse primer. The eight kinds of screening sets used in the present study were the same as those used in a previous study.(30) Each screening PCR product was run on a 2% agarose gel to identify the positive reaction among the eight kinds of screening sets. Finally, the TCR-BV gene family was identified by the second round of PCR using an individual TCR-BV gene family-specific forward primer, which was contained in the positive screening set, and the reverse primer. As a negative control, three PCR tubes without sorted cells were prepared in each experiment and were subjected to the same RT-PCR procedures.

A total of 750 WT1126 tetramer+ CD8+ T cells were analyzed in six patients (i.e. 59, 66, 46, 67, 88, and 73 cells from PT-1, -2, -3, -4, -5, and -6, respectively) and five HDs (i.e. 53, 57, 77, 79, and 85 cells from HD-1, -2, -3, -4, and -5, respectively). The International Immunogenetics Information System (IMGT) database site (http://www.imgt.org/IMGT_vquest/vquest?livret=0&Option=humanTcR, accessed 15 Nov 2011) was used to identify the human TCR-BV gene family.

Statistical analysis.  The Mann–Whitney U-test was used to evaluate differences in frequencies and subset compositions of WT1126 tetramer+ CD8+ T cells and CD3+ CD8+ T cells between patients and HDs. The significance of differences in usage frequencies of the 24 kinds of BV gene families between patients and HDs was also assessed using the Mann–Whitney U-test. Analyses were performed with the Stat Flex statistical software package (Artech, Osaka, Japan).

Results

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure Statement
  8. References
  9. Supporting Information

Increase in WT1126 tetramer+ CD8+ T cells with effector memory phenotype in HLA-A*0201+ patients with solid tumors.  The CTL responses to an HLA-A*0201-restricted epitope WT1126 of the WT1 protein were examined in HLA-A*0201+ patients with solid tumors. The PBMC were FACS analyzed by using WT1126 tetramer (Fig. 1), with Figure 1(a) showing representative profiles of the FACS analysis of WT1126 tetramer+ CD8+ T cells. The frequencies of WT1126 tetramer+ CD8+ T cells in patients and HDs were 0.007–0.122% (median 0.039%) and 0.009–0.079% (median 0.016%), respectively. Although there was a tendency for higher frequencies in patients than in HDs, the differences failed to reach statistical significance (data not shown).

image

Figure 1.  Frequencies of WT1126 tetramer+ CD8+ T cells in peripheral blood of patients with a solid tumor and healthy donors and phenotypic analysis of WT1126 tetramer+ CD8+ T cells. (a) Representative data of flow cytometric analysis using WT1126 tetramer. CD4, CD14, CD16, CD19, CD56, and WT1126 tetramer+ CD8+ T cells were defined as WT1126 tetramer+ CD8+ T cells. The percentages shown represent the frequencies of WT1126 tetramer+ CD8+ T cells among total CD3+ CD8+ T cells. (b) WT1126 tetramer+ CD8+ T cells were classified into four distinct differentiation stages according to the cell surface expression of CCR7 and CD45RA as follows: (i) CCR7+ CD45RA+ (naïve) cells; (ii) CCR7+ CD45RA (central memory) cells; (iii) CCR7 CD45RA (effector memory) cells; and (iv) CCR7 CD45RA+ (effector) cells. Representative data from Patient 3 are shown. (c) Frequencies of each subset of WT1126 tetramer+ CD8+ T cells. Closed and open circles represent patients and healthy donors, respectively. Bars indicate the median values of the frequencies.

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Human CD3+ CD8+ T cells can be divided into four distinct differentiation stages according to the cell surface expression of CCR7 and CD45RA as follows: (i) CCR7+ CD45RA+ (naïve) cells; (ii) CCR7+ CD45RA (central memory) cells; (iii) CCR7 CD45RA (effector memory) cells; and (iv) CCR7 CD45RA+ (effector) cells.(32,33) These cell surface markers were used to classify the differentiation stages of WT1126 tetramer+ CD8+ T cells and a representative pattern from PT-3 is shown in Figure 1(b). The frequency of the naïve phenotype of WT1126 tetramer+ CD8+ T cells was significantly higher in HDs than in patients (45.8–68.4% [median 55.6%] vs 3.4–37.9% [median 19.9%], respectively; < 0.01), while the frequency of the effector memory phenotype of WT1126 tetramer+ CD8+ T cells was significantly higher in patients than in HDs (30.3–58.6% [median 49.0%] vs 15.8–34.4% [median 20.7%], respectively; < 0.01; Fig. 1c). In contrast, there were no significant differences in frequencies of the four subsets of the whole CD3+ CD8+ T cells between patients and HDs (data not shown), indicating that the phenotypic difference in CD3+ CD8+ T cells between patients and HDs was restricted to WT1126 tetramer+ CD8+ T cells. These results demonstrate that WT1126 tetramer+ CD8+ T cells exhibit more differentiated/activated phenotypes in patients than in HDs.

Biased usage of TCR-BV gene families in WT1126 tetramer+ CD8+ T cells.  In the present study, TCR-BV gene families in WT1126 tetramer+ CD8+ T cells were investigated by using the single cell-based RT-PCR technique for the six patients and five HDs. Usage frequencies for a given BV gene family were defined as the ratio of the number of WT1126 tetramer+ CD8+ T cells with the usage of the BV gene family to the total number of WT1126 tetramer+ CD8+ T cells analyzed. When the usage frequency of a given BV gene family was more than the mean value + 1SD for the usage of 24 different kinds of BV gene families, the usage was defined as biased, as described previously.(30) As shown in Figure 2, the biased usage of the TCR-BV gene families was as follows: BV2, in two of six patients; BV3, in one of six patients and one of five HDs; BV4, in one of five HDs; BV5, in one of five HDs; BV6, in two of six patients and two of five HDs; BV7, in three of six patients and three of five HDs; BV9, in two of five HDs; BV11, in one of six patients; BV15, in one of six patients; BV19, in two of five HDs; BV20, in two of six patients and one of five HDs; BV27, in one of six patients and two of five HDs; and BV28, in two of six patients and two of five HDs.

image

Figure 2.  Frequencies of T cell receptor β-chain variable region (TCR-BV) gene families used by T cell receptors (TCRs) in WT1126 tetramer+ CD8+ T cells. The usage frequencies were defined as the ratio of (the number of a given TCR-BV gene family used)/(the total number of WT1126 tetramer+ CD8+ T cells analyzed). Closed columns indicate that the usage frequency is higher than the mean value + 1SD.

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The ratios of the number of patients or HDs with biased usage of individual TCR-BV gene families in WT1126 tetramer+ CD8+ T cells to the number of patients or HDs studied are shown in Figure 3. Nine TCR-BV gene families with biased usage were detected in patients and 10 were detected in HDs. These results show that: (i) BVs 3, 6, 7, 20, 27, and 28 are commonly biased in patients and HDs; (ii) BVs 2, 11, and 15 are biased only in patients; and (iii) BVs 4, 5, 9, and 19 are biased only in HDs.

image

Figure 3.  Usage frequencies of T cell receptor β-chain variable region (TCR-BV) gene families with biased usage in (a) patients and (b) healthy donors. The ratios show the number of patients or healthy donors with biased usage of the specific TCR-BV gene families to the total number of patients or healthy donors examined, respectively.

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The usage frequencies of TCR-BV gene families in patients reflect those in HDs.  The frequencies of 24 TCR-BV gene families used by T cell receptors (TCRs) of WT1126 tetramer+ CD8+ T cells were compared statistically between HLA-A*0201+ patients and HDs (Fig. 4). In all BV gene families, except BVs 5 and 19, the usage frequencies did not differ significantly between patients and HDs, although the subset compositions of WT1126 tetramer+ CD8+ T cells were significantly different between the two groups (see Fig. 1c). These results strongly indicate that the frequencies of TCR-BV families used by the TCR of WT1126 tetramer+ CD8+ T cells in patients with solid tumors reflect those in HDs.

image

Figure 4.  Statistical comparison of usage frequencies of individual T cell receptor β-chain variable region (TCR-BV) gene families in WT1126 tetramer+ CD8+ T cells between patients (PTs) and healthy donors (HDs). The significance of differences was assessed using the Mann–Whitney U-test. NS, not significant.

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Discussion

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure Statement
  8. References
  9. Supporting Information

Ratios of WT1126 tetramer+ CD8+ T cells with the effector memory phenotype were significantly higher in HLA-A*0201+ patients with solid tumors than in HLA-A*0201+ HDs, while those with the naïve phenotype were significantly lower in patients than in HDs, indicating that WT1126 tetramer+ CD8+ T cells were more activated and mature in patients than in HDs. These results are basically compatible with those of our previous study of WT1235 tetramer+ CD8+ T cells in HLA-A*2402+ patients with myeloid malignancies and HLA-A*2402+ HDs, where the frequencies of WT1235 tetramer+ CD8+ T cells were higher in patients than in HDs and WT1235 tetramer+ CD8+ T cells were more activated and mature in patients than in HDs.(30)

In order to analyze TCR-BV gene family usage of the TCRs of human tumor-associated antigen (TAA)-reactive T cells, two methods are routinely used: (i) bulky lymphocyte populations are FACS analyzed using a panel of mAbs directed against individual TCR-BV gene family products; or (ii) the populations are analyzed by PCR using a panel of TCR-BV gene family-specific primers.(34–40) However, the former method does not cover all the BV gene segments distributed in each BV gene family and the latter does not guarantee that all the TCR-BV gene families are amplified from the cDNA with equal efficiency. For example, TCR-BV gene families of T cells that exist at very low frequencies in lymphocytes are easily missed using this sort of PCR method.(40) In contrast, because the present study was performed at the single cell level and because the amplification efficiency of TCR-BV cDNA from a single WT1126 tetramer+ CD8+ T cell was >80% (data not shown), our results are thought to directly reflect TCR-BV gene family usage in WT1126 tetramer+ CD8+ T cells.

Regardless of a striking difference in WT1-specific CTL responses between patients and HDs, the usage patterns of TCR-BV gene families in patients were similar to those in HDs. That is, patients and HDs shared biased usage of TCR-BV families 3, 6, 7, 20, 27, and 28, while TCR-BV families 2, 11, and 15 were specifically biased in patients and TCR-BV families 4, 5, 9, and 19 were specifically biased in HDs. In total, six (3, 6, 7, 20, 27, and 28) of ten TCR-BV families (3, 4, 5, 6, 7, 9, 19, 20, 27, and 28) with biased usage in HDs also exhibited biased usage in patients. Three TCR-BV families (2, 11, and 15) newly emerged as those with biased usage specific to patients. However, in all BV gene families, except BVs 5 and 19, the usage frequencies did not differ significantly between patients and HDs. Together, these results led us to speculate that WT1-specific CTLs that had existed predominantly prior to the onset of the solid tumor had expanded and differentiated to maintain their dominance in tumor-bearing patients, whereas a few WT1-specific CTL populations with distinct TCR-BV families expanded in a tumor-bearing patient-specific manner. Furthermore, it may be suggested that WT1-specific CTLs with a dominant set of TCR-BV families in HDs play an important role in immune surveillance against tumors, and that the dominant populations continue to expand due to stimulation of the tumor-derived WT1 protein in WT1-expressing tumor-bearing patients. The immune response to WT1 may be unique, compared with other tumor-associated antigens, in the sense that WT1-specific CTLs are retained in healthy people at relatively higher levels, suggesting that precursors of WT1-specific CTLs are not deleted by the thymus, pass through it, and flow into the periphery. In fact, Pospori et al.(41) demonstrated that after murine hematopoietic stem cells transducted with the TCR gene of human HLA-A*0201-restricted WT1-specific CTLs had been transplanted into HLA-A*0201 transgenic recipients, surprisingly WT1-specific CTLs were not impaired by central or peripheral tolerance and, instead, differentiated into memory phenotype T cells. This suggests that precursors of WT1-specific CTLs are not deleted by the thymus. Thus, WT1-specific CTLs are likely to have some role in immune surveillance against tumors in both healthy people and patients with solid tumors. It appears reasonable that TCR-BV families that were appropriately selected for immune surveillance against tumors under healthy conditions were also preferentially used for immune surveillance under tumor conditions.

The question as to whether different TCR-BV families are used in distinct differentiation subsets of WT1126 tetramer+ CD8+ T cells was addressed in the present study. To resolve this issue, we analyzed differences in the usage frequencies of individual TCR-BV families between naïve and effector memory phenotypes, which are major and important phenotypes of WT1126 tetramer+ CD8+ T cells. However, only PBMC from HD-3 and -4 were available for this experiment because they were relatively abundant, while those from the other HDs and patients were too few in number to be analyzed. The WT1126 tetramer+ CD8+ T cells were divided into four cell populations of naïve, central memory, effector memory, and effector according to the cell surface expression of CCR7 and CD45RA, and both naïve and effector memory cell populations, which included more cells for the analysis, were provided for analysis of TCR-BV families. Eighteen naïve and nine effector memory cells from HD-3 and 26 naïve and 29 effector memory cells from HD-4 were FACS sorted and analyzed. As shown in Figure S1, available as Supplementary Material for this paper, usage frequencies of individual TCR-BV families were analyzed statistically between naïve and effector memory cell populations. In HD-3, no significant differences in usage frequencies of TCR-BV families were observed between naïve and effector memory cell populations. In addition, in HD-4, there were no significant differences in usage frequencies in most (13 of 15) of the TCR-BV families between the two cell populations, although the usage frequencies of only two TCR-BV families (i.e. BVs 12 and 19) were biased (= 0.0292 and = 0.0019, respectively). These results indicate that the usage pattern of TCR-BV families is similar between naïve- and effector memory-typed WT1-specific CTLs. These results also suggest that the patterns of biased usage of TCR-BV families does not change during the differentiation process from naïve to effector through central memory and effector memory.

In both patients and HDs, TCR-BV families 3, 6, 7, 20, 27 and 28 are preferentially used in WT1126 tetramer+ CD8+ T cells. As for TCR-BV families of CTLs for other TAAs, it has been reported that, in a melanoma patient, HLA-A2-restricted NY-ESO-1-specific CD8+ T cells preferentially used TCR-BV families 6, 9, and 12.(35) Among these three TCR-BV families, TCR-BV family 6 was also preferentially used by TCRs of WT1126 tetramer+ CD8+ T cells in patients and HDs in the present study, while TCR-BV family 9 was preferentially used by WT1126 tetramer+ CD8+ T cells in HDs. Thus, it is interesting to observe the phenomenon that a given set of TCR-BV families are preferentially used by certain TAA-specific CD8+ T cells and that some of these families are shared by different TAA-specific CTLs. However, the reason why dominant CTLs for different TAAs (WT1 and NY-ESO-1) shared the same TCR-BV families 6 and 9 is difficult to explain at present. One explanation may be that TAA-specific CTLs with TCR-BV families 6 and 9 have an important role in tumor immunity in the context of HLA-A2 restriction. Further investigations are needed to address this issue.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure Statement
  8. References
  9. Supporting Information

This study was supported, in part, by a Grant-in-Aid from the Ministry of Education, Science, Sports, Culture, and Technology and the Ministry of Health, Labor, and Welfare of Japan.

References

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure Statement
  8. References
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure Statement
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
cas_2163_sm_fS1.tif11733KSupporting info item

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