Proteome-Based Personalized Anti-Tumor Therapy

Our research team has focused its efforts on the application of the adult personalised therapy for neurooncology. This work resulted in the development of the individually tailored proteome-based anti-tumor cell preparations (PATCP) and systems with preset characteristics to be used in the complex therapy of the glial tumor and metastases of the brain the lung and breast cancer. For seven years we have been studying the personalised and molecular mechanisms of migration, homing, cell adhesion and pathotropism of adult cells to cancer cells in vitro and in vivo. We performed a comparative proteomic mapping of the proteins and a whole transcriptome profiling of the gene expression (WPPGE) of neural cells (СD 133+), which have been isolated from the olfactory sheath of the nose of a cancer patient, mobilized autologous hematopoietic (СD34+) cells and cancer (СD 133+) cells (Ccells), which have been isolated from the glial tumors of the brain (U87 and U251 glioblastoma multiforme lines) of the humans and animals (C6 rat glioma line), as well as the bioinformational processing and mathematical modeling of the obtained data. We detected global structural proteomic and transcriptomic differences of the studied adult cells and established the evidence that helped develop a novel platform of the personalized cytoregulatory effect on the reproductive and proliferative functions of the tumor cells by the specifically determined secretome of autologous cells with modified WPPGE.

  1. We have proven in the experiment that the patient’s cells always reach the tumor in the brain, find the cancer cells (CCs) an Ccells, adhere to them and affect them according to the bystander effect.
  2. Low efficiency of the anti-tumor regulatory and controlling effect of the cells on the CCs and Ccells is conditioned by the systemic mechanisms of speciation in the carcinogenesis that can be overcome by the specifically modified effector features of these cells based on the results of WPPGE.
  3. We have demonstrated that from 30 to 60 % of the species-specific proteins can be mapped in the Ccells proteome, and their bioinformation analysis help detect the intrapersonalised pathways of signal transduction (ICPST) that have not been involved into the carcinogenic neoplastic transformation and remain accessible for targeted regulator effects.
  4. The proliferative and reproductive functions of the tumor’s Ccells can be managed and controlled affecting known membrane target proteins of these ICPSTs in the Ccells.
  5. The available databases of the protein-protein interactions permit detection of the main ligand proteins that are able to activate the membrane target proteins of the ICPSTs in the Ccells and manage the effector functions of the Ccells.
  6. Use of this chemical induction helps modify the transcriptome profiles of the patient’s cells in specific direction avoiding gene engineering and develop the cell preparation from the autologous cells that express the necessary regulatory ligand proteins.
  7. We developed a special software for the search of perturbagens (chemical agents and microRNAs) in the Affymetrix databases. The perturbagens are able to modify the WPPGE to induce specific properties under certain conditions and exposition time.

We demonstrated that the cell systems with modified WPPGE effectively suppress reproductive and proliferative properties of the CCs and Ccells of the brain tumor in the experiment in the rat models of brain tumors and confirmed the efficiency of the proposed cytoregulatory therapy. We showed the role and place of the proposed cytoregulatory method of the anti-tumor treatment in the complex conventional and immune therapies of the brain tumors. We proposed a new paradigm of the systemic proteome-based anti-tumor therapy that aims to transfer the acute and fatal malignant process into chronic non-lethal disease by the control of the number of the CCs and regulation of the Ccells. Currently, the technology is protected by the Russian patent application; the Scientific Boards an Ethics Committees of the Russian Cancer Center of the Russian Academy of Science and Federal Medical-Biological Agency approved the clinical trials. The project is registered at www.clinicaltrial.gov ( NCT01782287 for Proteome-based Immunotherapy of Lung Cancer Brain Metastases http://clinicaltrials.gov/ct2/show/NCT01782287?term=NCT01782287&rank=1, NCT01782274 for Proteome –based Immunotherapy of Brain Metastases from Breast Cancer http://clinicaltrials.gov/ct2/results?term =NCT01782274+&Search=Search NCT01759810 for Proteome-based Personalized Immunotherapy of Glioblastoma, http://clinicaltrials.gov/ct2/results?term= NCT01759810+&Search=Search).

Provisional results of the proteome-based Therapy of different types of cancer

Table 1.

Distribution of the cancer cases at 3-4 stage into the control group and trial groups that receive precision IT

Cancer types

 

The number of the case files

The number of the cases in the trial group

The number of the cases in the control group

1.

Lung cancer

81

10

21

2.

Breast cancer

63

10

13

3.

Glioblastoma multiforme

72

11

12

4.

Kidney cancer

20

5

10

5.

Ovarian and uterine cancer

35

7

10

6.

Soft tissues sarcoma

38

5

10

7.

Stomach cancer

29

5

10

8.

Colorectal cancer

39

6

10

9.

Tumors of head and neck

16

3

7

10.

Melanoma

45

8

10

11.

Totally:

 

438

70

113

Table 2.

Distribution of the control group cancer cases at 3-4 stage by age and sex

Cancer types

 

Cases number

Sex

 

Age

 

 

 

male

female

male

female

1.

Lung cancer

21

14

7

56,5

64,6

2.

Breast cancer

13

-

13

-

54,7

3.

Glioblastoma multiforme

12

8

4

64,7

63,5

4.

Kidney cancer

10

5

5

62,6

63,5

5.

Ovarian and uterine cancer

10

-

10

-

48,5

6.

Soft tissues sarcoma

10

7

3

48,6

54,8

7.

Stomach cancer

10

10

-

66,2

-

8.

Colorectal cancer

10

8

2

56,2

51,2

9.

Tumors of head and neck

7

2

5

49,1

60,2

10

Melanoma

10

8

2

56,4

60,1

11.

Totally:

 

113

62

51

57,3

57,9

Table 3.

Distribution of the trial group cancer cases at 3-4 stage by age and sex

п/п

Cancer types

 

Cases number

Sex

 

Age

male

female

mal

female

1.

Lung cancer

10

8

2

64.1

63.3

2.

Breast cancer

10

-

10

-

52.7

3.

Glioblastoma multiforme

11

7

4

36.1

58.5

4.

Kidney cancer

5

5

-

55.6

-

5.

Ovarian and uterine cancer

7

-

7

-

52.1

6.

Soft tissues sarcoma

5

4

1

56,2

44

7.

Stomach cancer

5

4

1

56.2

61

8.

Colorectal cancer

6

3

3

54.3

51.8

9.

Tumors of head and neck

3

3

-

44.3

-

10

Melanoma

8

6

2

46.2

48.5

Table 4

Distribution of the control group patients with metastatic damage of the brain by the degree of compensation as measured by Karnofsky/ ECOG performance scales

Karnofskу/

ECOG

 

The number of breast cancer cases with metastases to the brain

The number of lung cancer cases with metastases to the brain

The number of GBM cases

 

%

score

abs

%

abs

%

abs

%

90

1

1

7.7

1

4,8

-

-

80

1

1

7.7

4

19

2

16.6

70

2

2

15.4

4

19

2

16.6

60

2

4

30.8

5

23.8

3

25

50

3

3

23.1

1

4.8

2

16.6

40

3

-

-

2

9.6

1

8.3

20-30

4

2

15.4

4

19

2

16.6

Table 5

Distribution of the trial group patients with metastatic damage of the brain by the degree of compensation as measured by Karnofsky/ ECOG performance scales

Karnofskу/

ECOG

 

The number of breast cancer cases with metastases to the brain

The number of lung cancer cases with metastases to the brain

The number of GBM cases

 

%

score

abs

%

abs

%

abs

%

90

1

-

-

1

10

1

9.1

80

1

1

10

1

10

2

18.1

70

2

2

20

2

20

2

18.1

60

2

4

40

3

30

1

9.1

50

3

2

20

1

10

1

9.1

40

3

1

10

1

10

2

18.1

20-30

4

-

-

1

10

2

18.1

Table 6.

The distribution of the 3-4 stage cancer cases depending on the immunotherapy strategy

 

 

Cancer types

 

 

The strategy of the proteome based adoptive immunotherapy (DV and CTL).

 

The strategy of using targeted proteome-based BCMPs.

 

The strategy of combined personalised-pharmaceutical remodeling of the antitumor function of the immunity (precision IT).

 

abs

%

abs

%

abs

%

1.

Lung cancer

10

14.3

10

33.3

8

16

2.

Breast cancer

10

14.3

7

23.3

7

14

3.

Glioblastoma multiforme

11

15.8

10

33.3

8

16

4.

Kidney cancer

5

7.2

-

-

2

4

5.

Ovarian and uterine cancer

7

10

-

-

3

6

6.

Soft tissues sarcoma

5

7.1

-

-

3

6

7.

Stomach cancer

5

7.1

-

-

4

8

8.

Colorectal cancer

6

8.5

2

6.7

5

10

9.

Tumors of head and neck

3

4.2

1

3.4

2

4

10

Melanoma

8

11.4

-

-

8

16

11.

Totally:

 

70

100

30

100

50

100

Table 7.

The efficiency of the antitumor IT in various types of cancers, stage 3-4

Cancer types

 

Deterioration

 

No effect

 

Effective

 

 

Highly effective

 

abs

%

abs

%

abs

%

abs

%

1.

Lung cancer

1

25

2

10.5

5

18.5

1

25

2.

Breast cancer

1

25

1

5.3

3

11.1

3

75

3.

Glioblastoma multiforme

2

50

3

15.7

5

18.5

-

-

4.

Kidney cancer

-

-

1

5.3

1

3.7

-

-

5.

Ovarian and uterine cancer

-

-

1

5.3

2

7.4

-

-

6.

Soft tissues sarcoma

-

-

1

5.3

2

7.4

-

-

7.

Stomach cancer

-

-

2

10.5

2

7.4

-

-

8.

Colorectal cancer

-

-

2

10.5

3

11.1

-

-

9.

Tumors of head and neck

-

-

2

10.5

-

-

-

-

10.

Melanoma

-

-

4

21

4

14.8

-

-

11.

Totally:

 

-

100

19

100

27

100

4

100

Table 8.

The life span of the breast and lung cancer patients with the metastases to the brain and the patients with glioblastoma multiforme in the trial groups

Cancer types

 

 

Time from the cancer diagnosis to death (control group)

 

 

 

Months

Time till the development of tumor focus in the brain (control group)

 

Months

Time from the cancer diagnosis to death (trial group)

 

 

 

Months

Time till the development of tumor focus in the brain (trial group)

 

 

Months

1.

Lung cancer

10.6

6.1

11.2

12.6

2.

Breast cancer

45.7

2.25

59.6

8.7

3.

Glioblastoma Multiforme

12.3

5.2

36

12.6

4.

Totally:

22.8

4.51

35.6

11.3

Table 9

Safety of the precision immunotherapy of cancer and other malignant neoplasms

Types of cancer

No adverse effects

 

 

Minimal adverse effects

 

 

Average severity adverse effects

 

Severe (life threatening) adverse effects

 

   

abs

%

abs

%

abs

%

abs

%

1.

Lung cancer

6

15.3

2

22.2

1

33,3

   

2.

Breast cancer

7

17.9

   

1

33,3

   

3.

Glioblastoma multiforme

5

12.9

3

33.3

   

2

100

4.

Kidney cancer

2

5.1

           

5.

Ovarian and uterine cancer

3

7.6

           

6.

Soft tissues sarcoma

3

7.6

           

7.

Stomach cancer

4

10.2

           

8.

Colorectal cancer

2

5.1

1

11.1

1

33,3

   

9.

Tumors of head and neck

2

5.1

           

10.

Melanoma

5

12.9

3

33.3

       

11.

Totally:

 

39

100

9

100

3

100

2

100

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