The pituitary tumor transforming gene 1 (PTTG-1): an immunological target for multiple myeloma

Novel antigens in non-small cell lung cancer: SP17, AKAP4, and PTTG1 are potential immunotherapeutic targets

Lung cancer is the leading cause of cancer deaths in both genders worldwide, with an incidence only second to prostate cancer in men and breast cancer in women. The lethality of the disease highlights the urgent need for innovative therapeutic options. Immunotherapy can afford efficient and specific targeting of tumor cells, improving efficacy and reducing the side effects of current therapies. We have previously reported the aberrant expression of cancer/testis antigens (CTAs) in tumors of unrelated histological origin. In this study we investigated the expression and immunogenicity of the CTAs, Sperm Protein 17 (SP17), A-kinase anchor protein 4 (AKAP4) and Pituitary Tumor Transforming Gene 1 (PTTG1) in human non-small cell lung cancer (NSCLC) cell lines and primary tumors. We found that SP17, AKAP4 and PTTG1 are aberrantly expressed in cancer samples, compared to normal lung cell lines and tissues. We established the immunogenicity of these CTAs by measuring CTA-specific autoantibodies in patients' sera and generating CTA-specific autologous cytotoxic lymphocytes from patients' peripheral blood mononuclear cells. Our results provide proof of principle that the CTAs SP17/AKAP4/PTTG1 are expressed in both human NSCLC cell lines and primary tumors and can elicit an immunogenic response in lung cancer patients.

PTTG1 expression is associated with hyperproliferative disease and poor prognosis in multiple myeloma

Background

Multiple myeloma (MM) is an incurable haematological malignancy characterised by the clonal proliferation of malignant plasma cells within the bone marrow. We have previously identified pituitary tumour transforming gene 1 (Pttg1) as a gene that is significantly upregulated in the haematopoietic compartment of the myeloma-susceptible C57BL/KaLwRij mouse strain, when compared with the myeloma-resistant C57BL/6 mouse. Over-expression of PTTG1 has previously been associated with malignant progression and an enhanced proliferative capacity in solid tumours.

Methods

In this study, we investigated PTTG1 gene and protein expression in MM plasma cells from newly diagnosed MM patients. Gene expression profiling was used to identify gene signatures associated with high PTTG1 expression in MM patients. Additionally, we investigated the effect of short hairpin ribonucleic acid (shRNA)-mediated PTTG1 knockdown on the proliferation of the murine myeloma plasma cell line 5TGM1 in vitro and in vivo.

Results

PTTG1 was found to be over-expressed in 36–70 % of MM patients, relative to normal controls, with high PTTG1 expression being associated with poor patient outcomes (hazard ratio 2.49; 95 % CI 1.28 to 4.86; p = 0.0075; log-rank test). In addition, patients with high PTTG1 expression exhibited increased expression of cell proliferation-associated genes including CCNB1, CCNB2, CDK1, AURKA, BIRC5 and DEPDC1. Knockdown of Pttg1 in 5TGM1 cells decreased cellular proliferation, without affecting cell cycle distribution or viability, and decreased expression of Ccnb1, Birc5 and Depdc1 in vitro. Notably, Pttg1 knockdown significantly reduced MM tumour development in vivo, with an 83.2 % reduction in tumour burden at 4 weeks (p < 0.0001, two-way ANOVA).

Conclusions

This study supports a role for increased PTTG1 expression in augmenting tumour development in a subset of MM patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s13045-015-0209-2) contains supplementary material, which is available to authorized users.

Pathway-based classification of cancer subtypes

Background

Molecular markers based on gene expression profiles have been used in experimental and clinical settings to distinguish cancerous tumors in stage, grade, survival time, metastasis, and drug sensitivity. However, most significant gene markers are unstable (not reproducible) among data sets. We introduce a standardized method for representing cancer markers as 2-level hierarchical feature vectors, with a basic gene level as well as a second level of (more stable) pathway markers, for the purpose of discriminating cancer subtypes. This extends standard gene expression arrays with new pathway-level activation features obtained directly from off-the-shelf gene set enrichment algorithms such as GSEA. Such so-called pathway-based expression arrays are significantly more reproducible across datasets. Such reproducibility will be important for clinical usefulness of genomic markers, and augment currently accepted cancer classification protocols.

Results

The present method produced more stable (reproducible) pathway-based markers for discriminating breast cancer metastasis and ovarian cancer survival time. Between two datasets for breast cancer metastasis, the intersection of standard significant gene biomarkers totaled 7.47% of selected genes, compared to 17.65% using pathway-based markers; the corresponding percentages for ovarian cancer datasets were 20.65% and 33.33% respectively. Three pathways, consisting of Type_1_diabetes mellitus, Cytokine-cytokine_receptor_interaction and Hedgehog_signaling (all previously implicated in cancer), are enriched in both the ovarian long survival and breast non-metastasis groups. In addition, integrating pathway and gene information, we identified five (ID4, ANXA4, CXCL9, MYLK, FBXL7) and six (SQLE, E2F1, PTTG1, TSTA3, BUB1B, MAD2L1) known cancer genes significant for ovarian and breast cancer respectively.

Conclusions

Standardizing the analysis of genomic data in the process of cancer staging, classification and analysis is important as it has implications for both pre-clinical as well as clinical studies. The paradigm of diagnosis and prediction using pathway-based biomarkers as features can be an important part of the process of biomarker-based cancer analysis, and the resulting canonical (clinically reproducible) biomarkers can be important in standardizing genomic data. We expect that identification of such canonical biomarkers will improve clinical utility of high-throughput datasets for diagnostic and prognostic applications.

Reviewers

This article was reviewed by John McDonald (nominated by I. King Jordon), Eugene Koonin, Nathan Bowen (nominated by I. King Jordon), and Ekaterina Kotelnikova (nominated by Mikhail Gelfand).

Novel strategies for immunotherapy in multiple myeloma: previous experience and future directions

Multiple myeloma (MM) is a life-threatening haematological malignancy for which standard therapy is inadequate. Autologous stem cell transplantation is a relatively effective treatment, but residual malignant sites may cause relapse. Allogeneic transplantation may result in durable responses due to antitumour immunity mediated by donor lymphocytes. However, morbidity and mortality related to graft-versus-host disease remain a challenge. Recent advances in understanding the interaction between the immune system of the patient and the malignant cells are influencing the design of clinically more efficient study protocols for MM. Cellular immunotherapy using specific antigen-presenting cells (APCs), to overcome aspects of immune incompetence in MM patients, has received great attention, and numerous clinical trials have evaluated the potential for dendritic cell (DC) vaccines as a novel immunotherapeutic approach. This paper will summarize the data investigating aspects of immunity concerning MM, immunotherapy for patients with MM, and strategies, on the way, to target the plasma cell more selectively. We also include the MM antigens and their specific antibodies that are of potential use for MM humoral immunotherapy, because they have demonstrated the most promising preclinical results.

Identification of AKAP-4 as a new cancer/testis antigen for detection and immunotherapy of prostate cancer

BACKGROUND

Prostate cancer (PC) is the second most common cancer in older men, after skin cancer. PC is difficult to diagnose because the prostate-specific antigen screening method is associated with many false positives. In addition there is a need to develop new and more effective treatments. Among presently available new treatments, immunotherapy is a promising approach. We investigated the expression of the cancer/testis antigen, AKAP-4, in PC patients to evaluate the possibility of exploiting AKAP-4 as a target for immunotherapy.

METHODS

We analyzed normal prostate tissues, 15 patients with PC and the LnCAP PC cell line by immunohistochemistry. We tested AKAP-4 immunogenicity through indirect ELISA on sera from patients and healthy subjects, and we generated in vitro AKAP-4-specific cytotoxic lymphocytes from peripheral blood mononuclear cells.

RESULTS

AKAP-4 was shown both at the cytoplasmic and surface levels of the LnCAP PC cell line. AKAP-4 was also highly expressed in PC cells from patients. We detected specific anti-AKAP-4 circulating immunoglobulins in AKAP-4 positive subjects. Using recombinant AKAP-4 loaded autologous dendritic cells, we generated AKAP-4-specific and HLA-I-restricted cytotoxic T lymphocytes able to kill PC cells in vitro. Further characterization indicated a Th-1 skewing in the cytokine secretion profile of these cells.

CONCLUSIONS

We demonstrate the aberrant expression of AKAP-4 in PC, which will potentially be developed as a biomarker in PC. We provide evidence that AKAP-4 is a potential target for PC adoptive immunotherapy or anti-tumor vaccination.

Mitotic chromosomal instability and cancer: mouse modelling of the human disease

The stepwise progression from an early dysplastic lesion to full-blown metastatic malignancy is associated with increases in genomic instability. Mitotic chromosomal instability - the inability to faithfully segregate equal chromosome complements to two daughter cells during mitosis - is a widespread phenomenon in solid tumours that is thought to serve as the fuel for tumorigenic progression. How chromosome instability (CIN) arises in tumours and what consequences it has are still, however, hotly debated issues. Here we review the recent literature with an emphasis on models that recapitulate observations from human disease.